{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "30e9afac",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import random\n",
    "import itertools\n",
    "from collections import Counter\n",
    "import re\n",
    "import datetime\n",
    "\n",
    "# Pycharm使用可将notebook改为tqdm\n",
    "from tqdm import tqdm, notebook\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99d7725b",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "## 所有函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "eb0b664f",
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "# 检查同花顺\n",
    "# nums--list, colors--list, 下同\n",
    "def check_straight_flush(nums, colors):\n",
    "    \n",
    "    for i in range(len(nums) - 1):\n",
    "        if nums[i+1] - nums[i] == 1:\n",
    "            continue\n",
    "        else:\n",
    "            return False  # 非同花顺\n",
    "    \n",
    "    if len(set(colors)) == 1:\n",
    "        return {'rank': 2, 'max': nums[-1]}  # 同花顺，比最大单牌 rank:2\n",
    "    else:\n",
    "        return False\n",
    "\n",
    "    \n",
    "# 检查四条和葫芦\n",
    "def check_four_three(nums):\n",
    "    \n",
    "    if len(set(nums)) == 2:  # 只有两种牌值，要么是四条，要么是葫芦\n",
    "        \n",
    "        c = Counter(nums)  # 统计牌值个数\n",
    "        m = list(set(nums))  # 两种牌值集合\n",
    "        \n",
    "        if c[m[0]] == 1:\n",
    "            return {'rank': 3, 'max': m[1]}  # 四条，比条值 rank:3\n",
    "        elif c[m[0]] == 4:\n",
    "            return {'rank': 3, 'max': m[0]}  # 四条，比条值 rank:3\n",
    "        elif c[m[0]] == 2:\n",
    "            return {'rank': 4, 'triple': m[1], 'pair': m[0]}  # 葫芦，比葫芦值再比对值 rank:4\n",
    "        else:\n",
    "            return {'rank': 4, 'triple': m[0], 'pair': m[1]}  # 葫芦，比葫芦值再比对值 rank:4\n",
    "    else:\n",
    "        return False  # 非四条、非葫芦\n",
    "\n",
    "    \n",
    "# 检查同花\n",
    "def check_flush(nums, color):\n",
    "    \n",
    "    if len(set(color)) == 1:\n",
    "        return {'rank': 5, 'max': max(nums)}  # 同花，比最大单牌 rank:5\n",
    "    else:\n",
    "        return False  # 非同花\n",
    "\n",
    "    \n",
    "# 检查顺子\n",
    "def check_straight(nums):\n",
    "    \n",
    "    for i in range(len(nums) - 1):\n",
    "        if nums[i+1] - nums[i] == 1:\n",
    "            continue\n",
    "        else:\n",
    "            return False  # 非顺子\n",
    "    return {'rank': 6, 'max': max(nums)}  # 顺子，比最大单牌 rank:6\n",
    "\n",
    "    \n",
    "# 检查三条和两对\n",
    "def check_three_pair(nums):\n",
    "    \n",
    "    if len(set(nums)) == 3:  # 有三种牌值，要不是三条、要不是两对\n",
    "        \n",
    "        c = Counter(nums)\n",
    "        m = set(nums)\n",
    "        single = [] # 储存三条外的个值\n",
    "        \n",
    "        if 3 in c.values():  # 如果某牌值有三个，则为三条\n",
    "            for i in m:\n",
    "                if c[i] == 3:\n",
    "                    triple = i\n",
    "                else:\n",
    "                    single.append(i)\n",
    "            return {'rank': 7, 'triple': triple, 'single_high': max(single), 'single_low': min(single)}  # 三条，三条先比条值，再比个值 rank:7\n",
    "        else:\n",
    "            pair = [] # 两对对值集合\n",
    "            for i in m:\n",
    "                if c[i] == 1:\n",
    "                    single = i  # 两对中的单牌\n",
    "                else:\n",
    "                    pair.append(i)  # 两对中的某值\n",
    "            return {'rank': 8, 'single': single, 'pair_low': min(pair), 'pair_high': max(pair)}  # 两对，两对先比对子，再比单牌 rank:8\n",
    "    else:\n",
    "        \n",
    "        return False  # 非三条、非两对\n",
    "    \n",
    "    \n",
    "# 检查一对\n",
    "def check_one_pair(nums):\n",
    "    \n",
    "    if len(set(nums)) == 4:\n",
    "        \n",
    "        c = Counter(nums)\n",
    "        m = set(nums)\n",
    "        single = []  # 单牌集合\n",
    "        \n",
    "        for i in m:\n",
    "            if c[i] == 2:\n",
    "                pair = i\n",
    "            else:\n",
    "                single.append(i)\n",
    "        single = sorted(single)\n",
    "        \n",
    "        return {'rank': 9, 'pair': pair, 'single_low': single[0], 'single_middle': single[1], 'single_high': single[2]}  # 一对，先比对子，再比单牌 rank:9\n",
    "    else:\n",
    "        return False  # 非一对\n",
    "    \n",
    "    \n",
    "# 比较单牌\n",
    "def check_high_card(nums):\n",
    "    \n",
    "    # return {'rank': 10, 'value_0': nums[0] + nums[1]*10 + nums[2]*100 + nums[3]*1000 + nums[4]*10000}\n",
    "    return {'rank': 10, 'value_4': nums[4], 'value_3': nums[3], 'value_2': nums[2], 'value_1': nums[1], 'value_0': nums[0]}\n",
    "\n",
    "\n",
    "# 底牌表示\n",
    "# i--str  eg: 'A3'--->♣️3\n",
    "def transfer_card(i):\n",
    "    \n",
    "    color = re.search(r'([A-D])(\\d*)', i).group(1)\n",
    "    num = re.search(r'([A-D])(\\d*)', i).group(2)\n",
    "    \n",
    "    if num == '1':\n",
    "        num = 14\n",
    "        \n",
    "    return {'color': color, 'num': int(num)}\n",
    "\n",
    "\n",
    "# 比较同牌值牌取最大\n",
    "# i--格式化后的卡牌{'rank':.., 'max?':..}\n",
    "def compare_samerank(i):\n",
    "    \n",
    "    rank = i[0]['rank']\n",
    "    position = 0\n",
    "    \n",
    "    # 牌型：单牌，比较方法：比最大单牌\n",
    "    if rank == 10:\n",
    "        out = i[0]\n",
    "        to_compare = list(i[0].keys())\n",
    "        to_compare.remove('rank')\n",
    "        \n",
    "        for m in range(len(i) - 1):\n",
    "            for z in to_compare:\n",
    "                if i[m+1][z] > out[z]:\n",
    "                    out = i[m+1]\n",
    "                    position = m+1\n",
    "                    break\n",
    "                elif i[m+1][z] == out[z]:\n",
    "                    continue\n",
    "                else:\n",
    "                    break\n",
    "        \n",
    "        return {'out': out, 'position': position}\n",
    "    \n",
    "    # 牌型：一对，比较方法：先比对子，再比单牌\n",
    "    elif rank == 9:\n",
    "        out = i[0]\n",
    "        to_compare = ['single_high', 'single_middle', 'single_low']\n",
    "        \n",
    "        # 比对子\n",
    "        for m in range(len(i) - 1):\n",
    "            if i[m+1]['pair'] > out['pair']:\n",
    "                out = i[m+1]\n",
    "                position = m+1\n",
    "                continue\n",
    "                \n",
    "            # 对子相同大小，从高到低比单牌\n",
    "            elif i[m+1]['pair'] == out['pair']:\n",
    "                for z in to_compare:\n",
    "                    if i[m+1][z] > out[z]:\n",
    "                        out = i[m+1]\n",
    "                        position = m+1\n",
    "                        break\n",
    "                    elif i[m+1][z] == out[z]:\n",
    "                        continue\n",
    "                    else:\n",
    "                        break\n",
    "            else:\n",
    "                continue\n",
    "        return {'out': out, 'position': position}\n",
    "    \n",
    "    # 牌型：两对，比较方法：先比高低对子，再比单牌\n",
    "    elif rank == 8:\n",
    "        out = i[0]\n",
    "        to_compare = ['pair_high', 'pair_low']\n",
    "        for m in range(len(i) - 1):\n",
    "            \n",
    "            # 比高对\n",
    "            if i[m+1]['pair_high'] > out['pair_high']:\n",
    "                out = i[m+1]\n",
    "                position = m+1\n",
    "                continue\n",
    "            elif i[m+1]['pair_high'] == out['pair_high']:\n",
    "                \n",
    "                # 比低对\n",
    "                if i[m+1]['pair_low'] > out['pair_low']:\n",
    "                    out = i[m+1]\n",
    "                    position = m+1\n",
    "                    continue\n",
    "                elif i[m+1]['pair_low'] == out['pair_low']:\n",
    "                    \n",
    "                    # 比单牌\n",
    "                    if i[m+1]['single'] > out['single']:\n",
    "                        out = i[m+1]\n",
    "                        position = m+1\n",
    "                        continue\n",
    "        return {'out': out, 'position': position}\n",
    "    \n",
    "    # 牌型：三条，比较方法：先比条值，再比高低单牌\n",
    "    elif rank == 7:\n",
    "        out = i[0]\n",
    "        for m in range(len(i) - 1):\n",
    "            \n",
    "            # 比条值\n",
    "            if i[m+1]['triple'] > out['triple']:\n",
    "                out = i[m+1]\n",
    "                position = m+1\n",
    "                continue\n",
    "            elif i[m+1]['triple'] == out['triple']:\n",
    "                \n",
    "                # 比高单牌\n",
    "                if i[m+1]['single_high'] > out['single_high']:\n",
    "                    out = i[m+1]\n",
    "                    position = m+1\n",
    "                    continue\n",
    "                elif i[m+1]['single_high'] == out['single_high']:\n",
    "                    \n",
    "                    # 比低单牌\n",
    "                    if i[m+1]['single_low'] > out['single_low']:\n",
    "                        out = i[m+1]\n",
    "                        position = m+1\n",
    "                        continue\n",
    "        return {'out': out, 'position': position}\n",
    "    \n",
    "    # 牌型：顺子、同花、四条、同花顺，比较方法：比最大单牌\n",
    "    elif rank in [6,5,3,2]:\n",
    "        out = i[0]\n",
    "        for m in range(len(i) - 1):\n",
    "            if i[m+1]['max'] > out['max']:\n",
    "                out = i[m+1]\n",
    "                position = m+1\n",
    "        return {'out': out, 'position': position}\n",
    "    \n",
    "    # 牌型：葫芦，比较方法：先比葫芦，再比对\n",
    "    elif rank == 4:\n",
    "        out = i[0]\n",
    "        for m in range(len(i) - 1):\n",
    "            if i[m+1]['triple'] > out['triple']:\n",
    "                out = i[m+1]\n",
    "                position = m+1\n",
    "            elif i[m+1]['triple'] == out['triple']:\n",
    "                \n",
    "                # 比对子\n",
    "                if i[m+1]['pair'] > out['pair']:\n",
    "                    out = i[m+1]\n",
    "                    position = m+1\n",
    "        return {'out': out, 'position': position}\n",
    "\n",
    "    \n",
    "## 得到C75最大牌型\n",
    "# cards_todo--公共牌{'color':.., 'num':..}\n",
    "# my_card--手牌\n",
    "def get_max_type(cards_todo, my_card):\n",
    "    \n",
    "    # 每种底牌得到最大牌值\n",
    "    types_todo = []\n",
    "    max_rank = 10\n",
    "    final_card = []\n",
    "    \n",
    "    for cards_ in itertools.combinations(list(cards_todo) + list(my_card), 5):\n",
    "        \n",
    "        # 获得排序后的牌值、花色集合\n",
    "        nums_ = []\n",
    "        colors_ = []\n",
    "        for x in cards_:\n",
    "            nums_.append(x['num'])\n",
    "            colors_.append(x['color'])\n",
    "        nums_ = sorted(nums_)\n",
    "        \n",
    "        # 储存当前组合内的最大牌型\n",
    "        max_type = ''\n",
    "        \n",
    "        if check_straight_flush(nums_, colors_):  # rank:2\n",
    "            max_type = check_straight_flush(nums_, colors_)\n",
    "            rank = max_type['rank']\n",
    "            \n",
    "        elif max_rank > 2 and check_four_three(nums_):  # rank:3 4\n",
    "            max_type = check_four_three(nums_)\n",
    "            rank = max_type['rank']\n",
    "            \n",
    "        elif max_rank > 4 and check_flush(nums_, colors_):  # rank:5\n",
    "            max_type = check_flush(nums_, colors_)\n",
    "            rank = max_type['rank']\n",
    "            \n",
    "        elif max_rank > 5 and check_straight(nums_):  # rank:6\n",
    "            max_type = check_straight(nums_)\n",
    "            rank = max_type['rank']\n",
    "            \n",
    "        elif max_rank > 6 and check_three_pair(nums_):  # rank:7 8\n",
    "            max_type = check_three_pair(nums_)\n",
    "            rank = max_type['rank']\n",
    "            \n",
    "        elif max_rank > 8 and check_one_pair(nums_):  # rank:9\n",
    "            max_type = check_one_pair(nums_)\n",
    "            rank = max_type['rank']\n",
    "            \n",
    "        else:  # rank:10\n",
    "            max_type = check_high_card(nums_)\n",
    "            rank = max_type['rank']\n",
    "        \n",
    "        # 如果当前牌值等于当前最大牌值，储存到待比较牌型\n",
    "        if rank == max_rank:\n",
    "            types_todo.append(max_type)\n",
    "            final_card.append(cards_)\n",
    "            \n",
    "        # 如果当前牌值比当前最大牌值还大，清空比较牌型\n",
    "        elif rank < max_rank:\n",
    "            types_todo = []\n",
    "            final_card = []\n",
    "            max_rank = rank\n",
    "            types_todo.append(max_type)\n",
    "            final_card.append(cards_)\n",
    "    \n",
    "    return {'types_todo': types_todo, 'rank': max_rank, 'board':list(cards_todo), 'hand':list(my_card), 'final':final_card}\n",
    "\n",
    "# 直观展示卡牌\n",
    "# i--经过position定位后的卡牌，未格式化 {'color':.., 'num':..}\n",
    "def display_cards(i):\n",
    "    \n",
    "    print('-----------------')\n",
    "    display_dict = {'A':'♣️', 'B':'♠️', 'C':'♦️', 'D':'♥️'}\n",
    "    out_dict = {'A':[], 'B':[], 'C':[], 'D':[]}\n",
    "    num_dict = {2:2, 3:3, 4:4, 5:5, 6:6, 7:7, 8:8, 9:9, 10:10, 11:'J', 12:'Q', 13:'K', 14:'A'}\n",
    "    for m in i:\n",
    "        out_dict[m['color']].append(m['num'])\n",
    "        \n",
    "    for m in out_dict.keys():\n",
    "        out_dict[m] = sorted(out_dict[m])\n",
    "        for z in out_dict[m]:\n",
    "            print('{}{}'.format(display_dict[m],num_dict[z]), end='')\n",
    "        if out_dict[m]:\n",
    "            print()\n",
    "\n",
    "# 直观展示卡牌等级\n",
    "# i--经过position定位后的格式化卡牌  {'rank':.., 'max?':..}\n",
    "def display_rank(i):\n",
    "    \n",
    "    num_dict = {2:'2', 3:'3', 4:'4', 5:'5', 6:'6', 7:'7', 8:'8', 9:'9', 10:'10', 11:'J', 12:'Q', 13:'K', 14:'A'}\n",
    "    rank_dict = {2:'同花顺', 3:'四条', 4:'葫芦', 5:'同花', 6:'顺子', 7:'三条', 8:'两对', 9:'一对', 10:'单牌'}\n",
    "    print('你的最终牌型：{}'.format(rank_dict[i['rank']]))\n",
    "    \n",
    "    if i['rank'] in [2,3,5,6]:\n",
    "        print('详细牌型：{}大'.format(num_dict[i['max']]))\n",
    "    elif i['rank'] == 4:\n",
    "        print('详细牌型：三条{}加对{}'.format(num_dict[i['triple']], num_dict[i['pair']]))\n",
    "    elif i['rank'] == 7:\n",
    "        print('详细牌型：三条{}加{}、{}'.format(num_dict[i['triple']], num_dict[i['single_high']], num_dict[i['single_low']]))\n",
    "    elif i['rank'] == 8:\n",
    "        print('详细牌型：对{}对{}加{}'.format(num_dict[i['pair_high']], num_dict[i['pair_low']], num_dict[i['single']]))\n",
    "    elif i['rank'] == 9:\n",
    "        print('详细牌型：对{}加{}、{}、{}'.format(num_dict[i['pair']],num_dict[i['single_high']],num_dict[i['single_middle']],num_dict[i['single_low']]))\n",
    "    else:\n",
    "        print('详细牌型：{}、{}、{}、{}、{}'.format(num_dict[i['value_4']],num_dict[i['value_3']],num_dict[i['value_2']],num_dict[i['value_1']],num_dict[i['value_0']]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1b1d74a",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "## 单次可视化测试--获得C75最大牌"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "id": "d56df1b1",
   "metadata": {
    "hidden": true,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "你的最终牌型：一对\n",
      "详细牌型：对9加A、Q、J\n",
      "-----------------\n",
      "♣️9\n",
      "♠️9♠️J\n",
      "♥️Q♥️A\n",
      "-----------------\n",
      "♣️9\n",
      "♦️4\n",
      "-----------------\n",
      "♠️9♠️J\n",
      "♦️8\n",
      "♥️Q♥️A\n"
     ]
    }
   ],
   "source": [
    "# 获得总牌库【card_list】\n",
    "# A-♣️, B-♠️, C-♦️, D-♥️\n",
    "# 11-J, 12-Q, 13-K, 14-A\n",
    "\n",
    "card_list = []\n",
    "\n",
    "for color in ['A', 'B', 'C', 'D']:\n",
    "    for num in range(2, 15):\n",
    "        card_list.append({'color':color, 'num':num})\n",
    "        \n",
    "exist_card = list(random.sample(card_list, 2))\n",
    "for x in exist_card:\n",
    "    card_list.remove(x)\n",
    "    \n",
    "## get_max_type输出\n",
    "# types_todo--某C75组合在最大牌级上输出的所有可能（已格式化）\n",
    "# rank--某C75组合最大牌级\n",
    "# board--当前公共牌\n",
    "# hand--当前自己手牌\n",
    "# final--某C75组合在最大牌级上输出的所有可能（未格式化，顺序与types_todo一一对应）\n",
    "h = get_max_type(random.sample(card_list, 5), exist_card)\n",
    "\n",
    "## compare_samerank输出\n",
    "# out--某C75组合最大牌型\n",
    "# position--该牌型对应types_todo中的顺序，为了拿到原始C75排列组合方便可视化输出\n",
    "k = compare_samerank(h['types_todo'])\n",
    "\n",
    "display_rank(h['types_todo'][k['position']])  # position为了定位，展示最终牌型等级及详情\n",
    "display_cards(h['final'][k['position']])  # 展示C75最大牌型\n",
    "display_cards(h['hand'])  # 展示手牌\n",
    "display_cards(h['board'])  # 展示公共牌"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25ba6912",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "## 所有牌型可能概率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 260,
   "id": "6b6c480e",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2dff69aae4b7490d90258c3cf43b16f7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/1000000 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{'单牌': '14.417%',\n",
       " '葫芦': '4.195%',\n",
       " '三条': '6.678%',\n",
       " '一对': '41.151%',\n",
       " '两对': '25.374%',\n",
       " '同花': '3.909%',\n",
       " '顺子': '3.662%',\n",
       " '四条': '0.590%',\n",
       " '同花顺': '0.024%'}"
      ]
     },
     "execution_count": 260,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 获得总牌库【card_list】\n",
    "# A-♣️, B-♠️, C-♦️, D-♥️\n",
    "# 11-J, 12-Q, 13-K, 14-A\n",
    "\n",
    "card_list = []\n",
    "count_rank = []\n",
    "\n",
    "for color in ['A', 'B', 'C', 'D']:\n",
    "    for num in range(2, 15):\n",
    "        card_list.append({'color':color, 'num':num})\n",
    "\n",
    "for i in notebook.tqdm(range(1000000)):\n",
    "    card_list_copy = card_list.copy()\n",
    "    exist_card = list(random.sample(card_list, 2))\n",
    "    \n",
    "    for x in exist_card:\n",
    "        card_list_copy.remove(x)\n",
    "        \n",
    "    h = get_max_type(random.sample(card_list, 5), exist_card)\n",
    "    count_rank.append(h['rank'])\n",
    "\n",
    "l = dict(Counter(count_rank))\n",
    "rank_dict = {2:'同花顺', 3:'四条', 4:'葫芦', 5:'同花', 6:'顺子', 7:'三条', 8:'两对', 9:'一对', 10:'单牌'}\n",
    "dict(zip(list(map(lambda x:rank_dict[x], l.keys())), list(map(lambda x:'{:.3%}'.format(x/1000000), l.values()))))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b6a971c",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "## 起始牌，蒙特卡诺模拟"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f80886e2",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cd9dcb33ea81439b9b04c7b293b50484",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/30000 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fb97444ec10>]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "simulation_time = 30000\n",
    "\n",
    "# 获得总牌库【card_list】\n",
    "# A-♣️, B-♠️, C-♦️, D-♥️\n",
    "# 11-J, 12-Q, 13-K, 14-A\n",
    "\n",
    "card_list = []\n",
    "count_rank = []\n",
    "\n",
    "for color in ['A', 'B', 'C', 'D']:\n",
    "    for num in range(2, 15):\n",
    "        card_list.append({'color':color, 'num':num})\n",
    "\n",
    "# 获得自己的手牌\n",
    "exist_card = list(random.sample(card_list, 2))\n",
    "# 设置手牌\n",
    "exist_card = [transfer_card('A1'), transfer_card('C5')]\n",
    "for x in exist_card:\n",
    "    card_list.remove(x)\n",
    "\n",
    "count = 0\n",
    "count_loss = 0\n",
    "count_win = 0\n",
    "count_tie = 0\n",
    "win_per = []\n",
    "loss_per = []\n",
    "count_list = []\n",
    "\n",
    "for i in notebook.tqdm(range(simulation_time)):\n",
    "    count += 1\n",
    "    \n",
    "    card_list_copy = card_list.copy()\n",
    "       \n",
    "    cards_todo_ = random.sample(card_list_copy, 5)\n",
    "    \n",
    "    # 当前底牌下，自己能够组合的最大牌型\n",
    "    my_max_cards = get_max_type(cards_todo_, exist_card)\n",
    "    \n",
    "    # 排除底牌和自己手牌后，对手可能的手牌池\n",
    "    for x in list(cards_todo_):\n",
    "        card_list_copy.remove(x)\n",
    " \n",
    "    opponent_cards = random.sample(card_list_copy, 2)\n",
    "        \n",
    "    # 当前底牌下，对手在某手牌中的最大牌型\n",
    "    opponent_max_cards = get_max_type(cards_todo_, opponent_cards)\n",
    "\n",
    "    # 如果对手牌型更大，则输\n",
    "    if opponent_max_cards['rank'] < my_max_cards['rank']:\n",
    "        count_loss += 1\n",
    "\n",
    "    # 牌型相同，则同牌型比大小\n",
    "    elif opponent_max_cards['rank'] == my_max_cards['rank']:\n",
    "        my_max_type = compare_samerank(my_max_cards['types_todo'])['out']\n",
    "        opponent_max_type = compare_samerank(opponent_max_cards['types_todo'])['out']\n",
    "        final_max_type = compare_samerank([my_max_type, opponent_max_type])['out']\n",
    "\n",
    "        if final_max_type == my_max_type and final_max_type == opponent_max_type:\n",
    "            count_tie += 1\n",
    "        elif final_max_type == my_max_type:\n",
    "            count_win += 1\n",
    "        else:\n",
    "            count_loss += 1\n",
    "\n",
    "    else:\n",
    "        count_win += 1\n",
    "        \n",
    "    if count % 100 == 0:\n",
    "        win_per.append(count_win / count)\n",
    "        loss_per.append(count_loss / count)\n",
    "        count_list.append(count)\n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a91476d",
   "metadata": {
    "hidden": true
   },
   "source": [
    "### 10w次模拟的胜率曲线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e2e6234c",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fb9824bcad0>]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(10, 3))\n",
    "ax[0].plot(count_list, win_per)\n",
    "ax[1].plot(count_list, loss_per)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8fd0ae83",
   "metadata": {
    "hidden": true
   },
   "source": [
    "### 5w次模拟的胜率曲线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f27629f1",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fb973a9afd0>]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(10, 3))\n",
    "ax[0].plot(count_list, win_per)\n",
    "ax[1].plot(count_list, loss_per)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9bb7eec5",
   "metadata": {
    "hidden": true
   },
   "source": [
    "### 3w次模拟的胜率曲线\n",
    "##### 总体来看，考虑耗时等因素，1w次的模拟能把胜率误差控制在+-1%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "839faa13",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fb97550fa50>]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(10, 3))\n",
    "ax[0].plot(count_list, win_per, color='red')\n",
    "ax[1].plot(count_list, loss_per, color='green')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c019926",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "## 获得起始底牌后，2人，蒙特卡洛模拟"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "8bef0d52",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dc21df6fdd1b481f8402f1c140275679",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/3 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f669884fc76c41f0a468dba7c16631c2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/100000 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8c30e4d2e785482fa2ad020a21589680",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/100000 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0a3349f2c0b543f29f5eb673a6920587",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/100000 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_list = []\n",
    "\n",
    "for round_time in notebook.tqdm([1, 2, 3]):  # 1--Flop、2--Turn、3--River\n",
    "    simulation_time = 100000\n",
    "\n",
    "    # 获得总牌库【card_list】\n",
    "    # A-♣️, B-♠️, C-♦️, D-♥️\n",
    "    # 11-J, 12-Q, 13-K, 14-A\n",
    "\n",
    "    card_list = []\n",
    "    count_rank = []\n",
    "\n",
    "    for color in ['A', 'B', 'C', 'D']:\n",
    "        for num in range(2, 15):\n",
    "            card_list.append({'color':color, 'num':num})\n",
    "\n",
    "    # 获得自己的手牌\n",
    "    exist_card = list(random.sample(card_list, 2))\n",
    "\n",
    "    # 设置手牌\n",
    "    # exist_card = [transfer_card('A1'), transfer_card('C5')]\n",
    "    for x in exist_card:\n",
    "        card_list.remove(x)\n",
    "\n",
    "    count = 0\n",
    "    count_loss = 0\n",
    "    count_win = 0\n",
    "    count_tie = 0\n",
    "    win_per = []\n",
    "    loss_per = []\n",
    "    count_list = []\n",
    "\n",
    "    # 起始三张公共牌\n",
    "    public_card = list(random.sample(card_list, 2+round_time))\n",
    "    # public_card = [transfer_card('B6'), transfer_card('B9'), transfer_card('C9')]\n",
    "    for x in public_card:\n",
    "        card_list.remove(x)\n",
    "\n",
    "    for i in notebook.tqdm(range(simulation_time)):\n",
    "        count += 1\n",
    "\n",
    "        card_list_copy = card_list.copy()\n",
    "\n",
    "        cards_todo_ = random.sample(card_list_copy, 3-round_time)\n",
    "\n",
    "        # 排除底牌和自己手牌后，对手可能的手牌池\n",
    "        for x in list(cards_todo_):\n",
    "            card_list_copy.remove(x)\n",
    "\n",
    "        cards_todo_ = cards_todo_ + public_card\n",
    "\n",
    "        # 当前底牌下，自己能够组合的最大牌型\n",
    "        my_max_cards = get_max_type(cards_todo_, exist_card)\n",
    "\n",
    "        opponent_cards = random.sample(card_list_copy, 2)\n",
    "\n",
    "        # 当前底牌下，对手在某手牌中的最大牌型\n",
    "        opponent_max_cards = get_max_type(cards_todo_, opponent_cards)\n",
    "\n",
    "        # 如果对手牌型更大，则输\n",
    "        if opponent_max_cards['rank'] < my_max_cards['rank']:\n",
    "            count_loss += 1\n",
    "\n",
    "        # 牌型相同，则同牌型比大小\n",
    "        elif opponent_max_cards['rank'] == my_max_cards['rank']:\n",
    "            my_max_type = compare_samerank(my_max_cards['types_todo'])['out']\n",
    "            opponent_max_type = compare_samerank(opponent_max_cards['types_todo'])['out']\n",
    "            final_max_type = compare_samerank([my_max_type, opponent_max_type])['out']\n",
    "\n",
    "            if final_max_type == my_max_type and final_max_type == opponent_max_type:\n",
    "                count_tie += 1\n",
    "            elif final_max_type == my_max_type:\n",
    "                count_win += 1\n",
    "            else:\n",
    "                count_loss += 1\n",
    "\n",
    "        else:\n",
    "            count_win += 1\n",
    "\n",
    "        if count % 100 == 0:\n",
    "            win_per.append(count_win / count)\n",
    "            loss_per.append(count_loss / count)\n",
    "            count_list.append(count)\n",
    "            \n",
    "        if count in [10000, 30000, 50000, 100000]:\n",
    "            plot_list.append({'round_time': round_time,\n",
    "                              'count': count,\n",
    "                              'win_per': win_per.copy(),\n",
    "                              'loss_per': loss_per.copy(),\n",
    "                              'count_list': count_list.copy(),\n",
    "                              'exist_card': exist_card,\n",
    "                              'public_card': public_card})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea128e5d",
   "metadata": {
    "hidden": true
   },
   "source": [
    "### Flop、Turn、River，不同次数的模拟曲线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "f6724f4a",
   "metadata": {
    "hidden": true,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "-----------------\n",
      "♦️5♦️6\n",
      "-----------------\n",
      "♠️5♠️10\n",
      "♥️K\n",
      "\n",
      "2\n",
      "-----------------\n",
      "♠️J\n",
      "♥️J\n",
      "-----------------\n",
      "♦️2♦️5♦️J\n",
      "♥️2\n",
      "\n",
      "3\n",
      "-----------------\n",
      "♣️5♣️8\n",
      "-----------------\n",
      "♣️6\n",
      "♠️7\n",
      "♦️2\n",
      "♥️7♥️K\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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AjqdEpCOuyXINMKzEd2FMuH37rWs6LIuEDFyfsqefhr/+Fd5+2zVNPujNFlOvnhs8YOs9lrWcAUsAIuIbsPRrwHF/BcYDncszuEPZh3I+Wx8yY6JfSBPDes2QqQHbRvl9fhF4sYhrzAJm+X2/shhxGlO+vvnGNVWefHLZ/k6zZvDAA+518CBs3Ojm/apdu2x/10DwAUt5/oGLSAqugt+D/AmZAl+IiAKvqurowB8oTR9YX3MlWIXMmMOBzdRvTDBffQUnneSmeygviYluMllTXkIZsPQ8cLeqZkn+vnxdVXWjiDQAvhSRZar6dZ6LuSRtNECnTp2KajXIw9dcCVYhM+ZwcPi0iezd66oPxhTlq6/ghx/gkksiHYkpW0UOWAI6AWO9gUkDgJdF5CIAVd3ovf8JfEIBA5NKyipkxhxeDp+E7P774dhj4c8/Ix2JKStZWW6+rNLIznad7Zs0cf27TDQrcsCSqrZU1RbewKSPgOGqOkFEqolIDQARqQacTZgHJvkmhQUbZWnM4eDwSci2bXMTe951V6QjMaFITy/6mECPPw5Nm+afRqI4xoxxk7z+85/lv26kKVeqmgn4BiwtBcb5Biz5Bi0VoiEwW0QWAXOAz1T183DG52uyTIhNsAqZMYeBwych8/0P/u23c2dgNxXTa6+5/lS1a7t+XD/+WPQ5GRluNvs9e9xM+EUO8g3i4EG3gPaJJ8IVVxT/fFPpqGqqqrZV1SNV9XFv2yj/QUt+x16jqh95n1eragfv1d53bjj5mizrVa1nfciMOQwcXgnZUUe5tQeHD4dDh4o+x0TGp5/CEUe4Geq3boWLL4bNmws/Z8IE1xzdv79buuiNN4r/uy++CH/8Af/+t005YSLOVyGrm1TXKmTGHAYOn//rpKe7hZEfewwWL4b58yMdkQkmM9NVMM8/3yVIn30Gu3fDpZcWnkS/8opbfHvsWOjWDe64A9auDX5sRobrK+Zv507XTHnuudC9e7juxpgSy6mQJdUjIyuDQ1n2l0hjotnhlZAlJEDr1u77zp2RjccEt3Cha3bs1s19P+44N5v97NnwyCPBz1m2DGbNcssQVamSWx3r2zfvP+e0NNeHsHp1iIuD+vXh+uvdCNwnn3Sz8//rX2V3b8YUg3+FDGzqC2Oi3eEzD1l6OtSqlTvh5q5dkYzGFGTWLPd+1lm52wYNgvfec9Wvxx7Lf86oUS7B+ou3Nn2rVq4Js08fuPBCePZZ14z50kuwfr1bH7JZM9c8+eab7jc3bHBNpB06lPENGhMa/woZuJGWtRNrRzAiY0xZOnwqZAcPugpZrVru++7dkY3ncPfll25Nx2XL8m6fNcv19WvcOO/2s8+GVavyN0MuWeISsssvhwYNcrd37+6WI/rmG+jcGe69101l8e23bvtjj7n3WbNcU6iqW0vSmAoisEJm/ciMiW6HV4XMErKK44MP4Pvv4fTTITUVunTJ7T82eHD+43v0cO8zZ8I117jP6eluNGTNmq4jfqDLL3ejNXftcgldYJIHbq3KxYvdgIDmzcN1d8aUmq9CZk2WxhweDq+ELDHRzS1VpYolZJE2Zw506gQ7drhk66OPXJ8u//5j/tq3h+RkmDEjNyF78EFYtAgmToSGDYP/zoUXFh1LjRruZUwF4psY1ipkxhweDp8mS1+FTMT1I7M+ZJGzZw8sXepGUn77LbRpA/36wZ13uv3+/cd8YmJcM+SMGa55cd48ePppGDrUXceYKJOvU7/N1m9MVDv8EjJwzZZWIYuc+fNdUtWlCzRqBF9/Db16uf5cRx/ttgXTvbvrfL9iBdxzD9St65IyY6KQ/8SwYBUyY6JdSAmZiPQRkd9EZKWI3BNkfzcR2S0iC73XgwH7Y0XkJxGZ7Letroh8KSIrvPc6pb+dQlhCVnHMneveO3d27zVqwKRJ8MAD7lUQXz+y++6D6dPdsTVrlm2sxkSITXthzOGlyD5kIhILvAT0BtYDc0Vkoqr+GnDoN6rar4DL3IZbK87//573ANNV9QkvybsHuLu4NxAyS8gqjjlz4MgjoV693G1xcfCPfxR+Xps2kJIC48e7SWBvLGq5QWMqr8BpL6xCZkx0C6VC1gVY6a3dlgGMBULoKe2ISBPgPOD1gF0XAm97n98GLgr1msWWne2mNrCErGKYM8c1VxaXSG6V7LHHcv95GhOFfBUy39xj1ofMmOgWSkKWAqzz+77e2xboVBFZJCJTRKS93/bngbuAgLVqaKiqmwC89waEy8yZbkSer2ksw41WyvkfuHXqj5xNm2DdupIlZAC33uqWRRo0KLxxGVPBpGemkxCbQNW4qghS4gpZtgY+eo0xFVEoCZkE2aYB3xcAzVW1A/ACMAFARPoBf6pqiReOFJGhIjJPROZt3bo19BO3bYN93t8o093fNK1CVgH4kuSSJmSdOtni3+awkJ6VTkKVBESEavHVStSHbPGfi4l/NJ6bP7uZvel7yyBKY0y4hPJ/tfVAU7/vTYCN/geo6h5VTfM+pwJxIlIf6ApcICJrcE2dPUTkPe+0LSLSGMB7/zPYj6vqaFXtpKqdkpOTQ7urpCT3fuCAew+WkO3dm3+BaVP25syB2Fjo2DHSkRhTofkqZADV4qqVqEL227bfyNIsXp73Mse9chy/bPkl3GEaY8IklIRsLtBGRFqKSDwwEJjof4CINBIR8T538a67XVXvVdUmqtrCO2+Gqg7xTpsIXO19vhr4tNR345OY6N4LS8hUXVJmytecOW7B8KpVIx2JMRVaRlYGCVXcM6t6fPUSVcj2Zrhn3HsXv8ef+/5k9PzRYY3RGBM+RY6yVNVMEbkFmArEAv9V1SUicqO3fxQwALhJRDKBA8BAVQ1s1gz0BDBORK4D/gAuLcV95OWrkB086N4DEzL/BcZ9SymZsueb0LV//0hHYkyFl57lVyGLr1aiTv2+ZspzWp9DSs0Uth/YHtYYjTHhE9LSSV4zZGrAtlF+n18EXiziGrOAWX7ftwM9Qw+1GEJpsgTrR1be1qyBnTtdPzBjTKHSs9KJj40HXIWsJE2WvgpZjfga1E2qy44DO8IaozEmfKKzZ7SvybKgCpklZJExb557t4TMmCKlZ6bnNFlWiytZp/696XuJi4kjoUqCJWTGVHDRmZBZhaximj/fTQB77LGRjsSYCs+/ybI0FbIaCTUALCEzpoI7vBMym4usfM2bB8cfbxO6GhOCPBWykvYhy9hLjXiXkNVLqmd9yIypwKIzIatSxU2tUFSnfquQlR9VVyE76aRIR2JMpZCnQhZXwgpZet4K2a6Du8jKzgprnMaY8IjOhAxclcxXIfMlZtZkGTmrV7uKpPUfMyYk+SpkJZz2wlch8y1SvuvgrrDFaIwJn8MjIfNVyHyd/RMS3MsSsvIz31uswSpkxoQkz7QXcdXYf2h/sZdBCqyQAdaPzJgKKnoTssTEgpsswVXJrA9Z+Zk3D+LjrUO/MSEKnBgWYP+h/cW6RmAfMsD6kRlTQUVvQhasQuafkNWubRWy8jR/vuvQHx8f6UiMySEifUTkNxFZKSL3FHJcZxHJEpEBAdtjReQnEZkc7tjyLJ0UXw2g2P3IrEJmTOURvQlZYmLhCZktMF5+fB36rf+YqUBEJBZ4CTgXaAcMEpF2BRz3JG61kkC3AUvLIr7AaS+AYo+0DNaHzBIyYyqm6E3IkpKKbrK0hKzsrVoF/fq5P+uuXSMdjTH+ugArVXW1qmYAY4ELgxz3V2A88Kf/RhFpApwHvF4WwQVODAvFq5CpKnvS91hCZkwlEd0JmVXIImv6dGjfHr7+Gp55BgYNinRExvhLAdb5fV/vbcshIinAxcAo8nseuAsoXk/7EAUunQTFS8gOZB4gW7OpmVATgNqJtRGE7futD5kxFVFIa1lWSomJsG2b++xLyPz7L1mn/rI3ciTUqwdz5kBKStHHG1O+JMg2Dfj+PHC3qmaJ5B4uIv2AP1V1voh0K/AHRIYCQwGaNWsWcmCqmqcPmS+p2pO+J+Rr+BYW9/Uhi42JpXZibauQGVNBRW9CFthkGRcHMX4FQevUX7Z274bPP4ebb7ZkzFRU64Gmft+bABsDjukEjPWSsfpAXxHJBE4GLhCRvkAiUFNE3lPVIf4nq+poYDRAp06dApO9AmVmZ6JoTpNlnaQ6AOw8uDPkm/NfWNynblJddhy0hMyYiujwabIMXK6nVi3Ytw8yM/Nu3xn6A88UYuJEyMiASy+NdCTGFGQu0EZEWopIPDAQmOh/gKq2VNUWqtoC+AgYrqoTVPVeVW3ibR8IzAhMxkojPctV9X0VsjqJLiErTnUrsEIGtp6lMRVZSAlZUUPDRaSbiOwWkYXe60Fve6KIzBGRRSKyREQe8TvnYRHZ4HdO3/DdFvnnIQuWkAHs8WsC+OEHqF8fVq4MaygVhirsL948RiU2bhw0bQonn1w+v2dMMalqJnALbvTkUmCcqi4RkRtF5MZIxpae6SVkgRWyA6WvkFkfMmMqpiITslCHhgPfqGpH7/UPb1s60ENVOwAdgT4icorfOc/5nZNaqjsJFEqFDPL2I1uxArKz3Xs0+t//IDnZLWMUKDMTliyBrBKuc7d7Nzz+uLvGrl3wxReuOhYTvUVYU/mpaqqqtlXVI1X1cW/bKFXN14lfVa9R1Y+CbJ+lqv3CGVdghSw+Np5qcdWK12QZpEJWr2o9q5AZU0GF8n/LUIeG56OOb1hQnPcKuR9FqYSakPn3I/M1V27ZUvbxRcJHH7kK2XPP5d/3yituFv2GDeHqq2Hz5tCv+/330LEj3H+/m2vs+uutudKYUsjIygByK2TgqmTBErJVO1bR5oU2rNu9Ls/2oBWyRGuyNKaiCiUhK3JouOdUr2lyioi09230ZrJeiJvD50tV/dHvnFtE5GcR+a+I1ClB/AXzNVmqBk/Iatd27/4J2Q7vQRWNCVlmJkyb5ipW//0vbA9othg/Hlq2hL59YexYeOih3H3Z2fDHH3mPX7cOnn7aHX/GGW7bpElw1lnuWs2aWXOlMSWU02QZ65eQJdYJ2mQ5Z8McVu5YyaIti/JsL6gP2a6Du8jKLmEl3BhTZkJJyEIZGr4AaO41Tb4ATMg5UDVLVTviRjB1ERHfYoavAEfimjI3Ac8E/XGRoSIyT0Tmbd26NYRwPUlJLhnLyAi9QuZLyP78k6jz44/uXu+/31XJXnkld9/27TB7NgweDO+8494/+AD2ugc6DzzgkjXfAuEHD8KZZ8Jdd8Hvv8Ott8LChW4C2NRUeOMNGD0aJNi/OsaYouQ0WfpVyArqkL9h7wYAtu7L+3wsqA+Zouw6uCvcIRtjSimUhKzIoeGqusfXNOn1BYsTkfoBx+wCZgF9vO9bvGQtG3gN1zSaj6qOVtVOqtopOTk5pJsCXIUMXLNlqH3IornJcupUVx0bMQL69IEXXsgd9JCa6vqOXei1RA8bBmlpLinbvNk1cWZnw//9n0tyX3oJ1qyBKVNg6VJ49tncP8+YGPjLX+CccyJxl8ZEhaAVsgKaLDfscQnZtv3b8mz3Vch8k8qC60MGNlu/MRVRKAlZkUPDRaSReBP1iEgX77rbRSRZRGp725OAXsAy73tjv0tcDCwu5b3klZTk3g8eLH6FLFoTsi5doE4duPNOVwX0VckmToTGjeGkk9z3k092C4G/+ir885+uynjbbTBrFrz3Hjz2mEvq+vSJ2O0YE818FTLfTP1QcJNlToVsf/4KWdW4qsTGxOZss+WTjKm4ipwYVlUzRcQ3NDwW+K9vaLi3fxQwALjJmzDxADBQVdVLut72RmrG4IaVT/Yu/ZSIdMQ1f64BhoX1znwJma9CVr163v2FdeqPtibL7dth7tzcfmHdu8N558Hf/w69erkJXAcPzh0RKQI33gjDh8OiRXDtta6/WGoqXHONq5I9+WTEbseYaBc47QV4CVmQCtn6PeuBIAlZ+t48zZVgCZkxFVlIM/V7zZCpAdtG+X1+EXgxyHk/AycUcM0rixVpcfk3WR486Jbw8RcXB9Wq5Z0INlorZNOmuSTK14woAq+95kZV9urlmicvuCDvOVdc4Spphw7Bgw+6P68nnoD+/V1Sdvzx5X4bxhwuAqe9AJdM7T+0P8+i41B4HzL/Dv2+awBsP2BzkRlT0UTvJFFFNVmCm5PLvxrmS862bi35fFzlTdXN+dW7N9xyS/BjpkxxTZWdO+dua9wYXn7Z3X/VqtCjR95zatZ0C4KPHOlGTAJcfLEbSTlyZNncizEGKKBCFmT5pGzNZuNe16U3Xx+yjPwVsnpJ1ofMmIoquteyhII79YObc8tXDVN1FbIaNdzowh07XMJWmH37glffysuhQ3D22a5vV2yse3/0UZd8+aSlwccfu2QqNjbv+ZdfDt9+6xIy35+Xv2EBrcgibiSlMaZMBauQ+ZZP2nlgJ42qNwJcVSwz2y3/FthkuSd9T74KWe3E2oAlZMZURNFbIfM1WRZWIfNPyHzrWh59tPseSrPliBGuI3x6elhCLrZp01wS9o9/wMyZLv5Jk/IeM2aMSzADkyufkSNdU6QxpsIoaGJYyFsh8/Ufa16ref4myyB9yGJjYqmdWNsSMmMqoOhNyIpbIfP1HytOQrZ8Oaxd6yZajYSxY90Et3fdBV27QpMmblJWf6NGwXHHwamnRiREY0zxBZv2IliHfF//sY6NOrI3Y2/OeeCaLGsm1Mx3bVtg3JiKyRKybdtcf7HAhCyUkZabNrn3f/3LTQ1Rng4cgE8+gUsucfcWE+M+T52aO6HrvHmwYIEbMWmTtBpTaQSbGNa/ydLHNwdZx0Ydgbz9yIJVyMD1I7NO/cZUPNGbkIXaZJmd7aaF8HXoP+YY9x5KhWzTJjdScd06eOutsIQdstRUl3gNHJi7rX9/d69Tprjvo0a5/mFXXFG+sRljSqWgiWEhb5Plhr0biJVY2ie71er8+5EFG2UJViEzpqKK3oQs1AoZuOTLVyFr1QqqVCk6IUtLc68hQ9yEq//8p1s+SMtn7XTGjoUGDdycYj5du7ptH3zgRki+/76bX8w355oxplIIViHzdcjPUyHbu4FG1RvldPL3VciysrPYf2h/0ApZ3aS6bN9vFTJjKproTch8FbI9e9x7UQmZr0JWr55LaopqsvQ1VzZu7JosN26EE06ANm3g++9LH39h9uyByZPhsstc8ugTG+tGU376qVvm6Mwz4eGHyzYWY0zY+SpkcTFxOduqxFShZkLNfJ36U2qmkFzNjQj3dexPy0gDCFoha1qzKev2rLMFxo2pYKI3IfNVyHxrVQZLyBo0cO/+FbI6dfJ29i/IRm85z8aN3RxeGza4BbXT0tzUE2Vl2za3VuTBg3mbK31uvRUGDIDp011/spSUsovFGFMm0rPSiY+NRwL6ftZJrJO3U/+eDTSp2YT6Vd3Swb4my2ALi/u0rdeWjKwM/tj9R1mFb4wpgehNyHwVMt/SSKFUyOLjXZ+rUBIyX4XsiCPce3Iy3HCDm8X+yy9d4hRuU6dCu3Zu7cnHH4fTTst/TLt28OGH+Sd6NcZUGumZ6Xn6j/kELjC+Ye8GUmqkUDepLjESk9Nk6VtYPFiFrG29tgAs3768LEI3xpRQ9CZkMTEuwSqsQla7tjvGVyGrU8eNRmzQIPSErHHjvNsHDnTzgX38cWnvIP/vXX65Sxbnz4f77rORk8ZEqfSsvMsj+fgvMJ6Wkcae9D2k1EghRmKol1Qvp8myqAoZhCch0/LqM2vMYSB6EzJwzZaFJWT+ydfOnVDXzfNDw4auD1lhD5tNm9w1/WfFB+jQAY46ynW6D6fbbnPNlOPHu3nFjDFRKyMrI2iFrG5S3ZwKmW/Ki5SarltC/ar1c5ssC6mQNajWgJoJNUudkB3KOkSL/7TgxTn5ljE2xpRA9CdkhTVZQm7y5auQ+balp+cOCAhm0yZo1Ch/lUrEVbJmzcqtopXWpEmuGfKBB6Bt2/Bc0xhTYRVWIfP1IfPN0p9SwyVkydWSQ+pDJiK0qduG5TtKl5DN3TiXP3b/wZSVU0p1HWOME90JWWJi4RUyyO0vtmNH3goZFN5suWlT/uZKn8svd9W1Dz8sUdh5ZGa6RcOPPRbuvLP01zPGVHiF9iHzmix9s/Q3qdkEgOSqySH1IQPXbFnaCtmM32cA8OP6H63p0pgwCCkhE5E+IvKbiKwUkXuC7O8mIrtFZKH3etDbnigic0RkkYgsEZFH/M6pKyJfisgK771O4HVLragmS8hNyHbuzK2Q+UZfFjb1RWEJWbt2cPzxMG5cicLOY/ly+OMPN41FfHzpr2eMqfAKqpDVTapLelY6Bw4dCN5kGUIfMnAJ2dpdazmYebDEMfoSsu0HtrN65+oSX8cY4xSZkIlILPAScC7QDhgkIu2CHPqNqnb0Xv/wtqUDPVS1A9AR6CMip3j77gGmq2obYLr3Pbz8myx9oy4D+Zost28PX4UM4IIL3Hxkvt8vqYUL3fuJJ5buOsaYSqPAClli7mz9q3eupk5iHarGVQVchWz7ge1ka3ZIFTJFWbVjVYniO3DoAN+t+44eLd1o7jkb5pToOsaYXKFUyLoAK1V1tapmAGOBC0O5uDpp3tc47+WrbV8IvO19fhu4KNSgQ5aYWPjEsOCqYYcOuWWIQk3IDh50FTXflBfB9OzplmX66quSxe6zcKGL3bfGpjEm6hXYh8xbPmnb/m1MXjGZ7i1zV+pIrpZMtmaz88BO9qTvIUZiSKqSFPT6pR1p+f3670nPSue2k28jqUoSP274sUTXMcbkCiUhSwHW+X1f720LdKrXNDlFRNr7NopIrIgsBP4EvlRV33+5DVV1E4D33qAkN1CoJL+HUWFNlj6+Jsv69V3n/IISsoKmvPB36qnu96dNCz3eYH76yfUfi4sr+lhjTFQoqkI28beJbE7bzOXtL8/Z5z857N4Mt7B44MSyPm3qtgFKnpBNXz2dWImle4vunHTESVYhMyYMQknIgv0XHdiDcwHQ3GuafAGYkHOgapaqdgSaAF1E5NjiBCgiQ0VknojM27p1a9En+PNvpgwlIfNVyKpUgWrVXNUsmFASsoQEt3RRaRIyVVch69ix5NcwxlQ6vpn6A9VNcs+o1xa8RlKVJM5rc17OvuSqbvmkLWlbmLlmJi1qtyjw+rUSa9GwWsMSJ2Qz1sygS0oXaiTU4OSUk1mwaQEZWRklupYxxgklIVsPNPX73gTY6H+Aqu7xNU2qaioQJyL1A47ZBcwC+nibtohIYwDvPWgPelUdraqdVLVTcnJyCOH6KWmFzHfugQPBzwklIQPXbLl0ae4yS6GYNAneeMN93rjRzfhvCZkxZaKoAUt+x3UWkSwRGeB9L3DAUjikZxbeZPnH7j/o17Yf1eKr5ezzrWf5/I/Ps/jPxdx3xn2F/kbbem1ZsWNFsWPbk76HuRvm5vQf65LShfSsdH7Z8kuxr2WMyRVKQjYXaCMiLUUkHhgITPQ/QEQaiVcbF5Eu3nW3i0iyiNT2ticBvYBl3mkTgau9z1cDn5byXvIrbkLmq5D5zi1tQtarl3ufPr3w4/z9859umotdu3I79FtCZkzYhTpgyTvuSWCq3+bCBiyVWkETw/qaLIE8zZWQ22Q5YdkEOh3RiQHtBhT6GyWd+mLSb5PI0qychOzklJMBrB+ZMaVUZEKmqpnALbiH0VJgnKouEZEbReRG77ABwGIRWQSMBAaqm5imMTBTRH7GJXZfqupk75wngN4isgLo7X0Pr1CaLOvVg9hY97k4FbLYWLd+ZWE6dHDXDzUhU4Vff3WDBsaNy03IOnQI7XxjTHGEOmDpr8B4/Kr4RQxYKrWCOvXXSqyFIFSLq8a5bc7Ns8/XZAnwZK8niZHCH+9t67Vly74t7D5Y+EjwfRn7cuYZ25exj3un30uHhh04q/lZADSr1YwG1RpYQmZMKVUJ5SCvGTI1YNsov88vAvnWz1DVn4ETCrjmdqBncYIttlAqZDExLrHavLl4FbKGDd25hYmJcYt8T5vmkq2i1p7csCF3VOibb0KTJtC6NdQIPnTdGFMqwQYsnex/gIikABcDPYDOAftigflAa+AlvwFLpVZQp/4YiaFR9UZ0b9k9Z7oLn4QqCdSvWp8TG5+YU70qzDH1jwFg7OKxDOs0LOgxBw4doPULrTmm/jGMv2w8z/3wHOv2rOP9S94nNsb9RVZEOKXJKXy37rvi3qYxxk9ICVmlFUpCBi652rzZLTbuf25hCVlRzZU+vXq5GfuXLYNjjin82CVL3Hu/fjB5MtSqBb17h/Y7xpjiCmXA0vPA3aqaFThiUVWzgI5et4xPRORYVV2c5wdEhgJDAZo1axZyYK+c90rODPyBvrzySxrXCP78mXblNJrVCu13+rTuQ69Wvbhlyi20qtOK3kfmf9ZMWTmFzWmb2Zy2mVPfOJU1u9Yw+LjBnNH8jDzH9WzZk4m/TWT1ztW0qtMqpN83xuQV/Usn+RSWkDVo4KpQ/lNLFJWQFTYHmb8+3hiGyZMLPw5yE7J//cs1ie7ebf3HjCk7RQ5YAjoBY0VkDa5rxssicpH/AUEGLPnvK9GgpIuPuZjOKZ2D7mvfoH3OaMtAHRp1yOn4X5S42Dg+uvQjjql/DP3H9Q/aKX/cknHUr1qfL4Z8wea0zVSJqcJTvZ7Kd1yf1u7Wp66cmm+fMSY00Z2Q+SpksbG5/cSCadXKNQ8GnhuOClmzZm4ZpVATsuRkN+/YuV7/EEvIjCkrRQ5YUtWWqtpCVVsAHwHDVXVCEQOWKo1aibVIvSKVpLgkbvv8tjz79h/az6Tlk+h/TH96H9mbhTcu5LvrvstZqslfm7ptaFm7pS00bkwpHB4JWWHVMXAVqSkBD5KCEjJV2Lo1d73LUJx/Pnz7rVvAvDBLlkB7b07dESNcMndK2AZuGWP8hDhgqSCFDViqVJrUbMI9Xe9h5pqZzP5jds721BWp7D+0P2c0Z4vaLTi+4fFBryEinNv6XGb8PoP0zPRyiduYaBPdCZmvybKohKxOHWjePO+2ghKy/ftdUlacjvbnnw9ZWfD55wUf4xth6UvIevaEtWvdKE1jTJlQ1VRVbauqR6rq4962Uf6DlvyOvUZVP/I+/6yqJ6jq8ap6rN/6vZXSsE7DaFCtAY9+/WjOtnFLxtGgWgPObH5mSNfo07oP+w7ty5PUGWNCF90JWagVsoLODZaQ+WbvL05C1rmzq6hNmlTwMevXu2u3b1/wMcYYUwaqxlXljlPv4ItVX/Dj+h/Zum8rk5dPZsAxA3JGUxale8vuxMfG8/nKz/l95++c8945fLz04zKO3JjoEd0JWagVsmCSktx8YIFKkpDFxMB557lm0UOHgh/j69DfLt+8lMYYU+aGdx5OvaR69H63Nw3+3YADmQcYfNzgkM+vHl+dM5qdwZjFY+jyehe+WPUFN6feTFpGWtEnG2OiPCErywpZ9erFu97557tRk7MLKOf7EjKrkBljIqB6fHVGnjuSnq168lj3x/j2L9/StVnXYl2jT+s+bNi7gbpJdXnnonfYnLaZZ757powiNia6HB7zkPlPf1GcczMyXN8v/xGaad7f9oo7WWvv3u6ca6+F8ePhpJPy7l+yxDVr1q8f/HxjjCljg48bXKyqWKAbTryBrOwshp40lDpJdZi4fCJPf/c0wzoNo1H1RmGM1JjoE90VstI2WUL+ZsuSNFmCq6hNmwbZ2dC1K3zwQd79/iMsjTGmEqqVWIu7T787Zy60f/X8F+lZ6dz02U1s3Js7xdvBzIM5yzEZY5zoTshK22QJ+ZstS5qQAXTpAgsWuOrY8OG5yV5WVt4RlsYYEwVa123NQ2c9xKfLPqX5883p9U4v2rzQhqTHk3j+h+cjHZ4xFYolZEWdG5iQ+Zosi9uHzKd+fXj4Ydef7LPP3LapU911zwxteLkxxlQW9595PytvXcmtXW5lc9pmjm94PEfVO4pX5r2Sr0qWlpHGkI+HMGvNrMgEa0wERXdCFo4my3BWyHx69HAz/b/7rvv+yituPc0LLyz5NY0xpoJqVacVz5zzDIuHL2b8ZeO55/R7WLFjBT+s/yHnGFVl6KShvP/L+9ww6QYOZRUwIt2YKBXdCVlpKmS+ZK6ghKykFTJwgwQGD4bUVPjpJ1cpu+46iI8v+TWNMaaS6H9Mf6rGVeWthW/lbHt57suMWTyG89qcx8odK3njpzciF6AxERBSQiYifUTkNxFZKSL3BNnfTUR2i8hC7/Wgt72piMwUkaUiskREbvM752ER2eB3Tt/w3ZanrPqQJSZClVIOUB0yxM1JNmCA+z50aOmuZ4wxlUSNhBoMaDeAsUvGcuDQAaasmMLfpv6Nfm37MXHQRE5vdjqPfPUI+zL2RTpUY8pNkQmZiMQCLwHnAu2AQSISbPbSb1S1o/fyLSOSCdyhqscApwA3B5z7nN85qaW7lSDKoskyLa10zZU+HTq4TvyrV7tJYwOXbjLGmCh2TYdr2JO+h0HjB9FvTD/aJbfj7YveJkZieLLXk2xO28zT3z0d6TCNKTehVMi6ACtVdbWqZgBjgZA6O6nqJlVd4H3ei1vAN6WkwRZbfDyIhL9CFo6ETMRVyQBuLGodY2OMiS5ntTiL5rWa8+lvn3LR0Rcx+y+zqZtUF4DTmp7Gpe0u5ZGvHmHE5yPIyMqIcLTGlL1Q2t1SgHV+39cDJwc57lQRWQRsBP5PVZf47xSRFsAJwI9+m28RkauAebhK2s5ixF40EZdYVcSEDODWW6F1a+gb/tZaY4ypyGIkhlf7vcrKHSu5qfNNxEje+sC7F79L4+qN+c+P/+HHDT8y8+qZJFYpwSTfxlQSoVTIJMi2wBn9FgDNVbUD8AIwIc8FRKoD44ERqrrH2/wKcCTQEdgEBF1fQ0SGisg8EZm3devWEMIN8O9/wzXXFP+8whKy0nTo91e1qutDJsH+iI0xJrqd0/ocbu5yc75kDCChSgL/Ofc/vNrvVX5Y/wPTV0+PQITGlJ9QErL1QFO/701wVbAcqrpHVdO8z6lAnIjUBxCROFwy9r6qfux3zhZVzVLVbOA1XNNoPqo6WlU7qWqn5OTkYtya56ab4MQTi39eWfchM8YYU6SrOlxFUpUkpq6aGnT/roO7gm7/cMmHNHuuGc99/1xOk+f6PevZvn97WYVqTKmEkpDNBdqISEsRiQcGAhP9DxCRRiKuzCMiXbzrbve2vQEsVdVnA85p7Pf1YmBxyW+jDJRHk6UxxphCJVZJpFuLbny+8vN8+5757hka/rshP236Kc/2zWmbGTZ5GLvTd3P7F7dz9ItH0/I/LWn6XFOaPteUe6bdw84D4e0hY0xpFZmQqWomcAswFdcpf5yqLhGRG0XE1xt9ALDY60M2EhiobgrmrsCVQI8g01s8JSK/iMjPQHfgb+G9tVKyhMwYYyqEPq37sGLHClbvXJ2zbd3udTw460EysjK4f+b9OdtVleGfDWf/of38eP2PpA5OpVmtZpzU+CSeP+d5+rfrz1PfPkWjZxrR7qV2XDT2IlbuWBmJ2zImj5Am0/KaIVMDto3y+/wi8GKQ82YTvA8aqnplsSItbwVNDJuWFr4+ZMYYY4p0zpHnADB15VRu6nwTAHd8cQfZms3wTsN5ed7LfPvHt3Rt1pUxi8fwybJPeKLnExxd/2iOrn8057Y5N8/17jztTt77+T1W7VzF1JVTuXva3Yy/bHy535cx/qJ7pv7SiIlxozP9EzJVq5AZY0w5a1uvLS1qt+DzVa7Zcvrq6Xz464fcd/p9PNX7KRpWa8h9M+7jkVmPcOUnV3JyysnccdodBV7v+IbH81Tvpxh/2Xj+2uWvTFg2gTW71pTT3RgTnCVkhUlKypuQHTgA2dmWkBljTDkSEc458hxm/D6DKSumcOmHl3JknSO5s+udVIuvxt/P+Dtfr/2ah796mMHHDebLK7+kSkxoq6kM7zwcQXhxTr5GHmPKlSVkhQlMyMKxjqUxxphi69O6D2kZafT9oC8pNVP44sovcuYlG3rSUK7qcBVvX/Q27178LjUSQv9Lc9NaTenfrj+vL3idPel7eGXuK1z+0eUcOHSg6JONCaNSLsgY5QITsrQ0924VMmOMKVc9WvagftX6dG3aNV/SlVAlgbcvervE1x5x8gjGLRlHu5fasWHvBgD6tenHlR0qdldnE12sQlaYgipklpAZY0y5qplQk/V/W8+EgROKVQELxSlNTuH0ZqdzIPMAb174Jm3qtmH0gtFh/Q1jimIVssJYQmaMMRVGQpUSLIMXAhHh8yvcgIFq8dXYtn8bd355J79u/ZV2ye3K5DeNCWQVssIkJcHBg7nfrQ+ZMcZEpWrx1agWXw2AqztcTXxsPKPnW5XMlB9LyApjfciMMeawk1wtmUuOuYR3Fr3D5OWTGf7ZcN786c1Ih2WinCVkhbEmS2Oimoj0EZHfRGSliNxTyHGdRSRLRAZ435uKyEwRWSoiS0TktvKL2pSHoScOZefBnZw/5nxemfcKf5v6Nw5mHiz6RGNKyBKywti0F8ZELRGJBV4CzgXaAYNEJF+HIe+4J3HLx/lkAneo6jHAKcDNwc41lVe3Ft0Ydd4oJg+azKRBk9idvptPl30a6bBMFLNO/YWxJktjolkXYKWqrgYQkbHAhcCvAcf9FRgPdPZtUNVNwCbv814RWQqkBDnXVFIiwrBOwwDIys6iac2mvLXoLS4/9vIIR2ailVXIChOsQpaQAHFxkYvJGBMuKcA6v+/rvW05RCQFuBgYRQFEpAVwAvBjkH1DRWSeiMzbunVrOGI2ERAbE8tVHa7ii1VfsHHvxkiHY6KUJWSFCZaQWXXMmGghQbZpwPfngbtVNSvoBUSq46pnI1R1T76LqY5W1U6q2ik5Obm08ZoIurrD1WRrNu/9/F6kQzFRyhKywvgSMvWe0Xv3Wv8xY6LHeqCp3/cmQGD5oxMwVkTWAAOAl0XkIgARicMlY++r6sdlHq2JqDb12tC1aVfeWvgWqoF5uzGlF1JCVtRIJBHpJiK7RWSh93rQ217gSCQRqSsiX4rICu+9TvhuK0ySktxi4ocOue9paVYhMyZ6zAXaiEhLEYkHBgIT/Q9Q1Zaq2kJVWwAfAcNVdYKICPAGsFRVny3vwE1kDDl+CEu3LWXZtmWRDsVEoSITslBHIgHfqGpH7/UPb1thI5HuAaarahtguve9YklKcu++ZktrsjQmaqhqJnALbvTkUmCcqi4RkRtF5MYiTu8KXAn08PuLaN8yDtlE2NlHng3AjN9nRDgSE41CGWUZ6kikfIoYiXQh0M079G1gFnB38cIvY/4JWa1aLiGrXTuiIRljwkdVU4HUgG1BO/Cr6jV+n2cTvA+aiWIta7ekea3mTP99Ojd3uTnS4ZgoE0qTZZEjkTynisgiEZkiIu0DdwYZidTQS9h8iVuD4gReLgIrZNZkaYwxhy0RoWfLnsxaM4us7KDjPIwpsVASslBGIi0AmqtqB+AFYEKeCxQxEqnQH4/ksPHERPduTZbGGGOAnq16svPgThZuXhjpUEyUCSUhK3IkkqruUdU073MqECci9aHQkUhbRKSxd0xj4M9gPx7RYePWh8wYY4yf7i26A7n9yJ79/llOef0UWo9szUmjTyp0eaVt+7fR9b9dGfPLmLDFcyjrEO8uepc96cWqdZgKKJSErMiRSCLSyBt1hIh08a67vYiRSBOBq73PVwMVb00K/4RM1aa9MMaYw1zjGo1pl9yO6b9P59Nln3LHF3eQmZ3JkXWPZMGmBXy99usCz319wet8t+47rvzkSj5Z+klY4rl3+r1cNeEqbvvcllOt7IpMyEIciTQAWCwii4CRwEB1E7UUNhLpCaC3iKwAenvfKxb/hCw9HbKyrEJmjDGHuR4tevD12q/5y8S/cGLjE/n2L9/yyeWfkBCbwOcrPw96TlZ2FqPmjeK0pqfROaUzA8cP5LPlnxX5W79u/ZWHZj5E97e789+f/ptnDrSPl37MM98/Q/NazXlr4Vt8tearsN2jKX8hzUOmqqmq2lZVj1TVx71to3yjkVT1RVVtr6odVPUUVf3O2z5bVUVVj/ebEiPV27ddVXuqahvvfUdZ3WSJ+SdkvoXFLSEzxpjDWs9WPTmQeYD0zHTG9B9DQpUEqsZV5awWZxWYkKWuSGXt7rXcfsrtpA5OpX1ye84fcz73z7ifzOzMoOf865t/0f7l9jz69aP8vvN3rpt4HeePOZ+Pl37MK3Nf4dpPr6VLShcW3riQFrVbcNNnN5GRlVGWt27KkM3UX5hgCZk1WRpjzGGte4vuHFXvKF47/zXa1mubs73PkX1Yum0pa3etzXfOS3Nf4ogaR3DBURdQJ6kO31z7Ddd2vJbHv3mc3u/25lDWoTzHf7/ue+6feT8D2g1gw+0bWH3bap475zmm/z6d/uP6Mzx1ODXia/DhpR9SO7E2L/V9iaXblvL0t0+X+f2bsmEJWWGsQmaMMSZArcRaLLtlGYOOG5Rne5/WfQCYumpqnu2/bv2VqaumMuykYcTFxgFQLb4ab1z4BqP7jWbWmlmMmpc7/d3e9L0M+WQIzWo1440L3qBxjcbESAwjThnBqltXMX/ofNb9bR2/3/Y7zWo1A6Bvm75c2u5SHv36UZZvX16Wt2/KiCVkhfFPyNLS3GdLyIwxxgRxdP2jaVarWU6z5aLNi7jykys54dUTqBpXlRtOvCHfOdefeD09Wvbgka8eYdfBXWRlZzF08lDW7FrDexe/R82EmnmOP6LGEZzY+ESa1GySk9z5jDx3JElxSQydNJRszS67Gy3A5rTNPDH7CTbs2VDuvx0NLCErjFXIjDHGhEhE6HNkH6atnsbT3z5Np9c68emyTxl20jB+GvYTjWs0DnrOM2c/w44DO3ho5kNc9tFljF08lsd7PE7XZl2L9fuNqjfimbOf4au1X/HGgjfCdVsh+XDJhxz78rHcO/1ejn3lWMb8MsYWYS8mS8gK45+QrfX6BDRqFLl4jDHGVGh9Wvdhb8Ze7pp2F+e3PZ+1I9Yy8tyRefqaBerYqCNXd7yakXNG8vHSj3nunOe45/SSLe98bcdr6dGyB3dNu4u0jLSS3kbIflz/I33f78tlH11GqzqtmHLFFI6pfwyDPx5M59c68/Csh1m6dWmZxxENLCErTFwcxMS4hGzOHKhXD1q0iHRUxhhjKqjeR/amd6vevHjui4y/bDx1kuqEdN7jPR7n5JSTefuitxlxyogS/76I8HiPx9l1cBfv//x+SOcs376cjXs3Bt2nqkErXZvTNnPR2Is45Y1TmLNhDk/1eorvrvuOPq378PW1XzOyz0gSqiTw6NePctLok1i2bVmJ7+lwIZWppNipUyedN29e+f5o9eowbBh8+SUccQR8HnxIszGmbIjIfFXtFOk4Sisizy9zWFJVTnj1BAB+GvYT3rzteRw4dIDnfniOD375gCVblwDQJaULQ44bwvDOw4mNiWX1ztX0+6Afuw7uol/bfvRo2YMjahzBlrQt3Jx6M3sz9vLAmQ/w1y5/pUZC8O48f+z+g5NGn0TTmk354fofiI+NL7sbr4CK8/yyCllRkpJg+3ZYsgQ6d450NMYYY0yhRISbOt3Eoi2L+GH9Dxw4dIBLP7yUKz6+glU7VvHH7j84480z+PuMv1M3qS4vnPsCj/d4nKzsLG79/FZ6vNODGb/P4Mw3z2TLvi2c1vQ0xi4ey6DxgzjrrbO47KPLOKLGEcwfOp/7zrivwGQMoFmtZrx+/uv8tPknHpjxQDn+KeTasGcD6ZnpEfnt4rAKWVGaNXNJ2fLl8OmncMEF5fv7xhzmrEJmTPHtTd9LyrMpnNf2PPam7yV1RSqJVRLJzM6kenx1sjSL9y95n35t++U5751F7zD8s+HsO7SPBtUaMO3KaRzX8DjSM9NZvn05W/ZtYV/GPvq07kNClYSQ4xk2aRivLXiNqzteze2n3M5xDY8L9y0HtfPATpo/35wOjTow7cppxYo5HKxCFk6+ZAysQmaMMaZSqJFQgyHHD2Hs4rF8tuIzRvUbxcpbV3JNx2s4JvkY5lw/J18yBnBVh6tYMGwBQ08cytfXfJ2TOCVUSeC4hsfRq1UvLjz6wmInNs/1eY5butzCuCXjOH7U8dw/4/4izzmYeZAHZjxAo383YvD4wcz+Y3axR25+8MsH7M3Yy+w/ZjNs8rA856sqP6z/ocJM02EVsqJ07AiLFkFKCqxfX76/bYyxCpkxJfTr1l857Y3TuP/M+/m/0/4v0uEAsOPADkZ8PoJ3f36XyYMmc17b8/Ido6pMXTWVEZ+P4Lftv9GzZU/mbpzLnvQ9tE9uz9CThnJVh6uonVi70N/y9aWLjYnlwqMu5KFZD3Fz55sZeOxAEmITuHva3cxcM5OE2ARu6nQT955xLw2qNQjr/Rbn+VUlrL8cjXxTX1h1zBhjTCXSLrkd2+7aRpWYivO/+rpJdRl9/mh++fMXrp5wNfOHzmf1ztV8vfZr4mPjSaiSwPu/vM+CTQtoWbslU4dM5ewjz2Zfxj7GLB7D6Pmjue3z23jq26eYc8McjqhxRIG/NW/jPBZtWcTLfV/mxk43snbXWl6a+xIvzX0pJ5bnznmOX7b8wsg5I3n353f56LKP6NaiW75rqSordqxg1ppZXNvx2nyT8oaDVciK0qMHzJwJjz8O991Xvr9tjLEKmTFRaPn25Zz46onsP7QfJW8e0qZuG+45/R6GHD8k6KjM2X/Mps97fTiu4XHMunpWnubT6auns3DzQoZ1GsYdU+/gvV/eY+PtG6mVWAuALWlbmLtxLut2r+PyYy+nblJdwFUT+4/rz8odK/lPn/9wU6ebEBFUlae+fYoX5rzAhr2uafPH63+kS0qXkO7TKmThZBUyY4wxJqza1mvL2AFjmbBsAn3b9OXsI8+mSkwV9qbvpV7VesRIwV3cT292Om9f9DYDPhzATZ/dxGvnv0ZsTCwfLvmQwR8PJjM7k6e+e4p9Gfu4rP1lOckYQMPqDYP2nWuX3I4frvuBKz6+gptTbyZ1RSr/6fMfHv36Ud5e9DbnHHkOD5z5AN1bdqdN3TZl8mcSUqd+EekjIr+JyEoRyTd9sIh0E5HdIrLQez3ot++/IvKniCwOOOdhEdngd07f0t9OGfAlZJ0q/V/QjTHGmAqjX9t+vH7B61xyzCVUj69OYpVEkqslF5qM+fRv158HznyANxe+SfPnm3Ptp9cycPxATmlyCtOunMYx9Y/hQOYBbup0U8jx1EqsxacDP+W5c55j5pqZtH6hNW8veptHuj3ClCumMKzTMNrWaxt0XrdwKLJCJiKxwEtAb2A9MFdEJqrqrwGHfqOq+dNOeAt4EXgnyL7nVPXfxQu5nLVs6apjdUKbbdkYY4wxZe+Rbo/QsVFH3lz4Ju8uepeeLXvyyeWfUC2+Gj1a9mDnwZ05TZKhio2JZcQpI7jwqAt5YOYD9G3Tl8HHDS6jO8grlCbLLsBKVV0NICJjgQuBwIQsKFX9WkRalDjCSHviCcjMjHQUxhhjjPEjIlxyzCVccswl7Dq4ixrxNYiNic3ZV9xkzF/LOi1575L3whVqSEJpskwB1vl9X+9tC3SqiCwSkSki0j7E379FRH72mjUrZgkqNhYSynciOWOMMcaErnZi7ZxkrLIKJSEL1lgaODRzAdBcVTsALwATQrjuK8CRQEdgE/BM0B8XGSoi80Rk3tatW0O4rDHGGGNM5RJKQrYeaOr3vQmQZ1l4Vd2jqmne51QgTkTqF3ZRVd2iqlmqmg28hmsaDXbcaFXtpKqdkpOTQwjXGGNCU9SAJb/jOotIlogM8NsWdMCSMcaURCgJ2VygjYi0FJF4YCAw0f8AEWkk3rADEeniXXd7YRcVkcZ+Xy8G7KFmjCk3fgOWzgXaAYNEpF0Bxz0JTA3Y9RbQp4zDNMYcJopMyFQ1E7gF9zBaCoxT1SUicqOI3OgdNgBYLCKLgJHAQPVmnBWRMcD3wFEisl5ErvPOeUpEfhGRn4HuwN/CemfGGFO4nAFLqpoB+AYsBforMB7403+jqn4N7CjzKI0xh4WQJob1miFTA7aN8vv8Im5qi2DnDipg+5Whh2mMMWEXbMDSyf4HiEgKroLfA7DZoY0xZaZSzdQ/f/78bSKytojD6gPbyiOeMlBZY6+scUPljb2yxg3Fj715GcURyoCl54G7VTWrJJNBishQYKj3NU1EfgvhtMr6z7ayxg2VN/bKGjdU3tjL7PlVqRIyVS2yV7+IzKus695V1tgra9xQeWOvrHFDhYq9yAFLQCdgrJeM1Qf6ikimqk4I5QdUdTQwujhBVaA/n2KprHFD5Y29ssYNlTf2soy7UiVkxhgTRjkDloANuAFLeabkVtWWvs8i8hYwOdRkzBhjiiOktSyNMSbahDhgqUCFDFgyxphii8YKWbGaByqYyhp7ZY0bKm/slTVuqECxFzVgKWD7NQHfgw5YCoMK8+dTTJU1bqi8sVfWuKHyxl5mcYs3O4UxxhhjjIkQa7I0xhhjjImwqErIQl0GpRzjaSoiM0VkqYgsEZHbvO11ReRLEVnhvdfxO+deL/7fROQcv+0neRPprhSRkb6VEco4/lgR+UlEJleyuGuLyEcissz7sz+1MsQuIn/z/j1ZLCJjRCSxosYtQZYNCmesIpIgIv/ztv8oIi3CfQ8VjT2/wh6/Pb/KP3Z7hpXmGaaqUfECYoFVQCsgHlgEtItwTI2BE73PNYDluCVangLu8bbfAzzpfW7nxZ0AtPTuJ9bbNwc4FTd30hTg3HKI/3bgA9zIMipR3G8D13uf44HaFT123CSlvwNJ3vdxwDUVNW7gTOBEYLHftrDFCgwHRnmfBwL/K+t/byL5wp5fZRG/Pb/KMXbsGVbqZ1jE/mMvgz/cU4Gpft/vBe6NdFwBMX4K9AZ+Axp72xoDvwWLGTf661TvmGV+2wcBr5ZxrE2A6bgZyn0PtMoQd03voSAB2yt07OTOGl8XN9hmMnB2RY4baBHwMAtbrL5jvM9VcBMxSlncR0V42fMr7LHa86v8Y7dnWCmfYdHUZBlsGZSUCMWSj1euPAH4EWioqpsAvPcG3mEF3UOK9zlwe1l6HrgLyPbbVhnibgVsBd70miteF5FqFT12Vd0A/Bv4A9gE7FbVLyp63AHCGWvOOeqmp9gN1CuzyCPPnl/h9Tz2/CrX2O0Zlmd7nnNCfYZFU0IWyjIoESEi1XGLE49Q1T2FHRpkmxayvUyISD/gT1WdH+opQbaVe9yeKrgy9CuqegKwD1d6LkiFiN3rq3Ahrhx+BFBNRIYUdkqQbZH6My9KSWKtiPdRlirs/drzK9/2slQpn19gz7CA7YWdU6BoSshCWQal3IlIHO5h9r6qfuxt3iIijb39jYE/ve0F3cN673Pg9rLSFbhARNYAY4EeIvJeJYjbF8t6Vf3R+/4R7gFX0WPvBfyuqltV9RDwMXBaJYjbXzhjzTlHRKoAtYAdZRZ55NnzK3zs+RWZ2O0ZVspnWDQlZDnLoIhIPK4T3cRIBuSNtngDWKqqz/rtmghc7X2+Gtc3w7d9oDc6oyXQBpjjlU73isgp3jWv8jsn7FT1XlVtoqotcH+OM1R1SEWP24t9M7BORI7yNvUEfq0Esf8BnCIiVb3f64mbPb6ix+0vnLH6X2sA7t/BSP8tuSzZ8ytM7PkVseeAPcNK+wwri45ykXoBfXEjgVYBf68A8ZyOK1H+DCz0Xn1x7cjTgRXee12/c/7uxf8bfiNLcIscL/b2vUg5dXAGupHbKbZSxA10BOZ5f+4TgDqVIXbgEWCZ95vv4kb0VMi4gTG4fiKHcH8TvC6csQKJwIfAStwoplbl8e97JF/2/CqTe7DnV/nGbs+wUjzDbKZ+Y4wxxpgIi6YmS2OMMcaYSskSMmOMMcaYCLOEzBhjjDEmwiwhM8YYY4yJMEvIjDHGGGMizBIyY4wxxpgIs4TMGGOMMSbCLCEzxhhjjImw/wcsnct7a3h9BAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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F9+WX7s/h229z7lu1yiVn/gmO7zV0qCuzdatqzZqqF12k2qJF9jILF+Z+3cWLs8rFxbmkqU4dt3766aq1a7vl+HiXsH33neqRIy6JOOss1UsuyUoyvvnGlT37bLd+0UVZ5+7d2207diznZxg4MPhn278/Z7y/+Y1LVtasOdVvOjxOnFBNSnI1Zfv3u/UHH1Tt2NF9t/PmqZ486cru2eOS659/Vl2/3pUNo1hMyL7f+r0yGu36n66hf1HGmIhjCZkpuAkT3J/Dxo25l5k1S/WPf3Qd2RMSXCJTpozqlCk5k7CpU1WvusotX3FF7uf829+yjunWTfXwYdWlS1VHjVJNTXVlpk3LSswg67zff5/zfD//rLpzp1s+dkz1iy9c2fHjs8r4ztOwoWrfvlnrjz6q2rq16qRJbv2vf3WfY/Zs1e3b3fXANeWVRtOmuf9uLVpkb4oePjzckeUpFhMyXw1Zl1e7hP5FGWMiTkHuX76RkaVC586ddcGCBfkXNKH7+Wf47jvYuhVGj3Yd3nOb1NRHFQ4dcmWbNnWP+Kle3XUiL1PGLbdt68o++KB7DNCyZa6jvb/UVGjWzM1S/8wz0KJF7p3E9+xx83Jt3OjWmzd3c36F0ql89mx3rG8y0ssug08/dZ3Ty5WDZ591y//4R9bn69/fTU/hr1o19/k2by69s+bPng033AC7drnPm5YGd93lptCIUCKyULM/dq1UKsj9a/aW2Vzw+gWcU/8c5t82v5gjM8YUl4Lcv0KZh8yUFvPmucSmXz83azy4kYVvveXmozr99OzljxxxiQ1A+/ZQp07+yRi4JKhaNbd88cUuubnmGrjoopxl77wTnnsOhg1zI/TmznXL5cq5eal274a//MXNcJ+XOnVc8njXXW4OrpdfDn2E3/nnZ1+fNMmNyPTNKH/PPTk/35tvuolXu3d3idzcuW5E4//9X+lNxsB9F2vWuElkGzXKv7wJC9/oShtlaUzssIQsmjzxhJsKYfJkV+NxxRXwzTdu2gpw/xOuUSOr/GefZS0vWQKdT6ES4o47XELmSwAD1ajhJky9+WY3Yzu4mD76CD7+2D0iqGfP0K/39NNutvvCPLWhYkVXM5eX2rXhscey1vv1O/XrRZoKFdzLRKx0TQcsITMmlhRyQiQTMVTh++/d8wPbtXM1SampLvnxWbQo+zHffece3XPDDW49JaXg1+3Txz3L0ZdsBXPttXDbbVnrn37qHji9YAF07VqwuawSEgqXjBnjR0T6ichaEdkgIiPzKHeOiKSLyCC/bZtFZLmILBGRIu1L4UvENMdT6owx0coSsmixfj3s2we9e7s+UVu2uNqpRx+F005zZfr0cU1uPr6+Vc8+69avuOLUrh3KQ6wffhj+9jdXM5aW5h7v88svp1YrZ0wREJF44CWgP9AGGCIibXIp9yRucuxAvVS1fVH3cUvPsBoyY2KNJWTR4q233PsFF7i+XJdc4jqqQ/baKd/s+ps2uVnre/Z0/bMOHy7emferV4ennoIBA9yyT6dOxXdNY/LWBdigqhtV9QQwCbg8SLnbgSnk8rzd4pBZQ1aKBl0ZYwrHErJokJwMTz4JQ4a4h08DvPuue7xRWhrcey+ULeu216/vmhj/+lf3CB/fA6wrV84ahVicEhPdiMtvv3Ud/jt2LP5rGhNcA2Cb3/p2b1smEWkAXAkEPIcLAAW+FJGFIjIs2AVEZJiILBCRBfv27Qs5MOtDZkzssU790WD5cvd8xVtvzdpWvbobAekzf77ry7VtG1x+OXz1les7Fo6Rdg0butcFF5T8tY3JEqzzYmCV1BjgXlVNl5x9Hbur6k4RqQ3MEJE1qvpdtpOpjgfGg5v2ItTArA+ZMbHHasgi1cmTWU2O+Vm71r37aseCadvWNV0ePeqSsSefhDfeKHycxpRe2wH/XyQNgZ0BZToDk0RkMzAIeFlErgBQ1Z3e+17gI1wTaJGwPmTGxJ6QErL8RiKJSE8ROeSNNloiIg8E7I8XkcUi8qnfttEissPvmAGF/zhRpFcvNzXBp5+60ZLHjkHfvvD11znLrlvnOtY3bJj3Of1rw+6+u2SaKI2JXD8BLUSkmYgkAoOBT/wLqGozVW2qqk2BycCfVHWqiFQUkcoAIlIR6AusKKrArA+ZMbEn3yZLv5FIfXC/KH8SkU9UdVVA0dmqemkup7kTWA1UCdj+L1V9poAxx4bvv3fvl10Gv/+9a36cMcNN+9C7d/aya9e6We7j8smvfQlZfLybcd6YGKaqaSIyAjd6Mh6YqKorRWS4tz9YvzGfOsBHXjNmGeAdVf28qGKziWGNiT2h/F85cyQSgIj4RiIFJmRBiUhDYCDwKHD3KcYZ2954w83CD+5xPh99BFde6dbT010fsrzmAfNp2tS9Dx9eLGEaU9qo6jRgWsC2oImYqg71W94ItCuuuKxTvzGxJ5Qmy3xHInm6ichSEZkuImf6bR8D/B0IdmcZISLLRGSiiFQPsj92+c+k3ry564z/2GNu+eqr3UhFcI/42boVBg0Kfh5/9erBypXu0UPGmIhlnfqNiT2hJGShjERaBDRR1XbAi8BUABG5FNirqguDnGMccDrQHtgFPBv04qc4bLxUO37cdb4fPNhNnrpqFRw4AKNGuWcqVq0K993nyk6c6B7afe21oZ27TRvrO2ZMhLNO/cbEnlASsnxHIqnqYVVN8ZanAQkiUgvoDvzGG6E0CegtIm955faoarqqZgCvkssIJVUdr6qdVbVzUlJSwT5daeVLPHv1cs+k9Fe9Oowc6Z5DOX26a8rs379gjx8yxkQ060NmTOwJJSHLdySSiNQVr3eriHTxzpusqqNUtaE3Qmkw8LWq3uiVq+d3iispwhFKpd5eb0Lw2rWD77/9dtcfbMAANz1GQR7ObYyJeNaHzJjYk2+n/hBHIg0C/igiacAxYLDmP177KRFpj2v+3Az84ZQ/RbTx1ZDllpBVqACff+6aKffuhR49Si42Y0yxs2kvjIk9Ic19kN9IJFUdC4zN5xyzgFl+6zcVIM7Y4qshy6uJ9owzYOlSULXmSmOijPUhMyb22Ez9kWjXLveeWw2ZP0vGjIk61ofMmNgT3QnZpEluFGJps3w5NGjgRlMaY2KOTXthTOyJ7oRsyBD43e/CHUXuZsyAsUFaehctgo4dSz4eY0xEsE79xsSe6E7IfLZvD3cEcOiQewTS5MlZ2/r2dSMmjx/P2vbrr7BmjSVkxsQw69RvTOyJ7oSsbFn37nvsUDh99x1MmADXXAM7dmTft2BB1vLSpZCRYQmZMTHMOvUbE3uiOyE7+2z3vnhxeOMA2LMna/nLLyEtLWt9zpys5UWL3LslZMbErNz6kM3fMZ/vt34fjpCMMcUspGkvSq0y3sdLSQlvHJCVkNWo4WbYP//8rH0zZkCVKjBmDKxb56a7aBDscaHGmFiQWx+yc/9zLgD7/76f6uXt8b/GRJPoriFLdzc1Tp4MbxzgErIqVeDCC90Dvtetc9vPPx9mzoQ//SlrW716Np2FMTEstz5kVcpWAeDVRa+WeEzGmOIV3QlZhvfr8sSJ8MXw5pvuEUe7d0OdOi7Z2r0bli1z+30PCQf46iv3ft55JR+nMSZi5DYPWetarQHYk7InxzHGmNItupssI6GG7OuvXRNllSrQtq1Lyvbvd82UbdrAJZfAO++4JKxJEzfCsmHD8MVrjAm73Dr1n8xw97Lj6cdzHGOMKd2shqy4JSe798OHXTJWt65b//pr91BwETdfWpMmbvsZZ0DFimEJ1RgTGXKrITuZ7hKyE+lhvKcZY4pFdCdkkVBDtn9/1nKdOu7lc+GFJR+PMSbi+Tr1+2rEfNIy3OhsqyEzJvpEd0IWKTVkvuk36tfPqiED6Nw5PDEZYyKafw2Zfy2ZL0GzGjJjok9ICZmI9BORtSKyQURGBtnfU0QOicgS7/VAwP54EVksIp/6bashIjNEZL33XvRjuCOhhiw5Gbp3d3OPDR+ePSFr1ix8cRljIpavD1ngcmYNWZrVkBkTbfJNyEQkHngJ6A+0AYaISJsgRWeranvv9XDAvjuB1QHbRgIzVbUFMNNbL1q+GrJwJWQZGa7JsmZN6NPHvfs3WdrUFsaYIPxrxXxJGFgfMmOiWSg1ZF2ADaq6UVVPAJOAy0O9gIg0BAYC/wnYdTnwhrf8BnBFqOfM1/r1bjqJTZvceriaLA8dcklZzZpZ28qVc+9XXx2emIwxEc/XhwwCEjIbZWlM1Apl2osGwDa/9e3AuUHKdRORpcBO4K+qutLbPgb4O1A5oHwdVd0FoKq7RKR2sIuLyDBgGEDjxo1DCBeXiD3+eNZ6uGrIfCMs/RMycE8O8D1n0xhjAuRWQ+ZbthoyY6JPKDVkwdrVNGB9EdBEVdsBLwJTAUTkUmCvqi481QBVdbyqdlbVzklJSaEdFB+ffT1cNWS5JWQVK2Y91skYEzb59Y/1K3eOiKSLyKCA7Tn6xxYFa7I0JvaEkpBtBxr5rTfE1YJlUtXDqpriLU8DEkSkFtAd+I2IbMY1dfYWkbe8w/aISD0A731vYT5INoEJWbhqyHxTXtSoEZ7rG2NyFWr/WK/ck8AXQU4TrH9soQXryA9+TZbWqd+YqBNKQvYT0EJEmolIIjAY+MS/gIjUFXE91EWki3feZFUdpaoNVbWpd9zXqnqjd9gnwC3e8i3Ax4X+ND6RXkNmjIkEofaPvR2YQsCPxjz6xxaaNVkaE3vybTdT1TQRGYH7dRgPTFTVlSIy3Nv/CjAI+KOIpAHHgMEa+FTcnJ4A3heR3wFbgWsK8TmyC2wOjLQ+ZMaYSJBv/1gRaQBcCfQGzgk4fgzB+8cWmn+nfl+tmKraxLDGRLGQOjJ5zZDTAra94rc8FhibzzlmAbP81pOBi0IPtQAipckyOdlNbVGtWniub4zJSyj9Y8cA96pquvhNU+PfP1ZEeuZ6gVMZlET2GjJfvzH/JM1qyIyJPtHZszySmiyrV88ZjzEmEuTbPxboDEzykrFawACvJeBcXP/YAUA5oIqIvOXXJQNwg5KA8QCdO3fOr9UgU7Dky5eYgfUhMyYaxUZCFs4aMmuuNCZSZfaPBXbg+rle719AVTMfpyEirwOfqupU3EjyUd72nripfrIlY4XhX0OWmZD5PdfSasiMiT6xkZCFs4bMRlgaE5FC7B8bFv6jLH3Jl6//WEJcgvUhMyYKxUZCFs5pL/yfXWmMiSj59Y8N2D40l+2z8OsfWxT8a8hS01K56/O7uKzlZQBUTKxIyomUorycMSYChPRw8VInkmrIrMnSGFNA/gnZpoObeH7e8/R9qy8AFRMqkpaRlq2MMab0i42ELCMD0tODly1OlpAZY06Bf6f+YyePAVlJWsXEioD1IzMm2kR/Quabk6ykmy1PnHDPrLSEzBhTQP61X0dOHMm2r1JiJcBGWhoTbaI/IStXzr2XdEK2ZYt7t4TMGFNA6RnplI0vC8DB1IPZ9lVMsBoyY6KRJWTFZfRod+0BA0r2usaYUi9DMyifUB6AQ6mHsu3zNVnaSEtjokt0JmT+j07yJWQl3bH/s8/gppugSZOSva4xptRL13TKlXH3roPHD2bbZzVkxkSn6EzIwl1DduiQe7VsWXLXNMZEjQzNoHwZV0MW2GRZIaECYH3IjIk2sZOQJSfD3r0lc31f/7ECPLvOGGN8MjQjq4YsICHzdeq3GjJjoktICZmI9BORtSKyQURGBtnfU0QOicgS7/WAt72ciMwXkaUislJEHvI7ZrSI7PA7pug6WwVLyDp0gDp1iub8a9a4qTRys3Wre7fmSmPMKUjPSM81IfM1WVofMmOiS74z9YtIPPAS0Af3MN6fROQTVV0VUHS2ql4asO040FtVU0QkAZgjItNV9Udv/79U9ZlCfoacgiVkRWXtWmjd2nXaHzjQ9Vdr3z5r/7x5cJmbUdsSMmPMqQilU7/VkBkTXUKpIesCbFDVjap6ApgEXB7KydXxPeMjwXvpKUVaEMWZkO3Y4d4//hh69HA1b99957apwl13ZZWtXbtor22MiQnpmk5CXAJxEpd7DZn1ITMmqoSSkDUAtvmtb/e2BermNU1OF5EzfRtFJF5ElgB7gRmqOs/vmBEiskxEJopI9VOIP7jiTMh8/dAOHoTj3g3xiSfguefgz3+GH3/MKhsXnV30jDHFK0MziI+LJzE+kWNpx7LtsxoyY6JTKBmDBNkWWMu1CGiiqu2AF4GpmQVV01W1PdAQ6CIiZ3m7xgGnA+2BXcCzQS8uMkxEFojIgn379oUQLsWbkO3c6d43bcraNn063HMPjBsHt94Kv/yS1Y/MGGMKKD0jnTiJIzE+Mce+yomVAXIkasaY0i2UhGw70MhvvSGw07+Aqh72NU2q6jQgQURqBZQ5CMwC+nnre7xkLQN4Fdc0moOqjlfVzqraOSkpKaQPla1mKjAhS0sL7Ry52bUr7/1DhrjZ+Rs1yrucMcbkIkMziJf4oAlZjfI1ADhy/EiOfcaY0iuUhOwnoIWINBORRGAw8Il/ARGpKyLiLXfxzpssIkkiUs3bXh64GFjjrdfzO8WVwIpCfpbgAhOy44Xsd7FzZ/b1rl2zr3foULjzG2NiXrq6GjLf45P8ZSZkJywhMyaa5DvKUlXTRGQE8AUQD0xU1ZUiMtzb/wowCPijiKQBx4DBqqpe0vWGN1IzDnhfVT/1Tv2UiLTHNX9uBv5QtB/NE5iQpaZCxYqnfr5du6BVKzf1BbiaMF+/scaNoVat3I81xpgQ+PchC+RLyA4fP1zSYRljilG+CRlkNkNOC9j2it/yWGBskOOWAUGrjFT1pgJFeqrKl8++fuwU+l3s2eOmufjnP10NWdu2WQnZ3XfDBx+40ZUtWhQ2WmOMIUMzcu1DVimxEglxCTmaLE+mnyTxkUTG9h/Ln7v8uaRCNcYUkZASslItsDYsNdW9Z2S4aSr8BwDk5vzzYf16975tG/TvD4MHw5QprslSi38mD2NM7MirU3+ZuDJUKVslRw3Z3l/dCPD7v77fEjJjSqHon5cht4SsSRM466yc5QMdOeKSMYAFC+DoUVcT9vbbWecyxpgilFen/oT4BCqXrZyjD9meX/dk7jfGlD6xW0O2fXtox/ueSwnw9dfuvUULm2PMGFNsfJ36C1JDtifFJWTxEkKtvzEm4kR/VlGhQvb1wFqtw/l0jN28OWt56VL3bn3FjDHFKK9O/QlxCVROzFlDtjtlN+ASNmNM6WMJ2Yp8ZtvwJWQdO7r3xESbY8wYU6x8fciCNT9mNlkeD95kaQmZMaVT9CdkCQnuAeA+gQmZ7zmUudmyxU2d4XuAeMuWoQ0EMMaYU+TrQ5Zywj0KuEWNrFr5eInPs8nSZvA3pnSK/oQsPt4lZT6+hKysN+Hi/ffDqlW5H795MzRtCtWqufVRo4ohSGNMOIhIPxFZKyIbRGRkHuXOEZF0ERnkrZcTkfne83tXishDRRmXrw+ZrxmyZc2W/rEEb7L81ZVNPpqM2shvY0qd6E/I4uKy12ilprppKo4fh2uucdNfLF4c/NjDh2HWLGjTxiViU6a4RyMZY0o9b8Lql4D+QBtgiIi0yaXck7jJsX2OA7295/e2B/qJSNfAY0+Vbx6ywITsjJpnAORZQ5au6Rw6fqioQjHGlJDoT8ji47OPiExNzaola9XKvft33Pc3bpx7UPioUW4G/quuAgn2rHVjTCnUBdigqhtV9QQwCbg8SLnbgSnAXt8GdVK81QTvVWTVUr4my9Q0d69qWKUhAK2TWgPuAeMpJ1LI0IzMY9Ylr8tcTj6aXFShGGNKSGwkZP5JVGpq1mz9NWpAUlL2qS38zZwJ7dpB587FH6cxpqQ1ALb5rW/3tmUSkQa4Z+2+QgARiReRJbhEbYaqziuqwHyd+v3XAdrWbgu4GjJwj09an7yeLq92YceRHVx82sUA/HL0l6IKxRhTQqJ/OE5cXM4aMl9CVr686x8WLCFLT3fPqLypZJ7wZIwpccGquwNrucYA96pqugTUjqtqOtBeRKoBH4nIWaqabdi2iAwDhgE0btw45MD6Ne9H+7rtmX3rbBbvWsxN7W5i++Ht/K373wBok+RaVudum8vsrbP5aedPAFza4lK+2vhV5ohLY0zpEf0JWWCT5bFj2ROyJk1g2bKcx61c6WbpP++8konTGFPStgP+c9g0BHYGlOkMTPKSsVrAABFJU9WpvgKqelBEZgH9gGwJmaqOB8YDdO7cOeQmzdeveD1zuUfjHgA83//5zG29mvWiUmIlPl77MVXLVs3cPrDlQO764i52HdkV6qWMMREipCbL/EYiiUhPETkkIku81wPe9lxHIolIDRGZISLrvffqRfex/ATr1B9YQ7Z1a87nUfoeHt62bbGEZYwJu5+AFiLSTEQSgcHAJ/4FVLWZqjZV1abAZOBPqjpVRJK8mjFEpDxwMbCmpAIvV6YcfU7rw5c/f8mWQ66G/7XLX6NptaYIws4jgXmlMSbS5ZuQhToSCZitqu2918PetrxGIo0EZqpqC2Cmt1708upDVr68m+Q1NRWSAzrBHjjg3mvWLJawjDHhpappwAjc6MnVwPuqulJEhovI8HwOrwd8IyLLcIndDFX9tHgjzq5TvU5sOriJlftW0rtZb4a2H0qZuDLUrljbEjJjSqFQmiwzRyIBiIhvJFIek3c56ibDyW0k0uVAT2/5DWAWcG+IcYcuvz5k9eu75V273EhKH19CVr14Ku6MMeGnqtOAaQHbcnTg97YP9VteBnQo1uDycXadswFYsXcFQ9sPzdxev3J9dqVYk6UxpU0oTZb5jkTydPOaJqeLyJm+jXmMRKqjqrsAvPfap/IB8pVfH7J69dzyzoBflPv3u8ljy5cvlrCMMaYwzqp9VuZyk6pNMpfrV67PZ+s/4/Zpt4cjLGPMKQolIQtlJNIioInXNPkiMDWzoGq6qrbHdZjtIiJnUQAiMkxEFojIgn379hXkUCewhiwtLXgNWWBCduCA1Y4ZYyJW02pNM5fb1WmXuewbDTr2p7E2Y78xpUgoCVm+I5FU9bBvkkSvCSBBRGoFlDmIa5bs523aIyL1ALz3vQShquNVtbOqdk5KSgoh3ACBNWTp6cFryHb5VfEPHw7/+Y+bp8wYYyJQnMTx1pVv8e7V73JFqysytydVyLpPbj64ueQDM8acklASsnxHIolIXfF+lolIF++8yfmMRPoEuMVbvgX4uJCfJbjAGrLAhKxcOVcT5l9D9u9/u3erITPGRLAb2t7A4LMGZ9aKATx3yXM8389NkbF4dy6PhTPGRJx8E7IQRyINAlaIyFLgBWCw16E/r5FITwB9RGQ90MdbL3qBNWSBTZbgmi0DmyzBEjJjTKlTrVw1hnUaRpm4Mrw4/0U+XP1huEMyxoQgpIlh8xuJpKpjgbFBjst1JJKqJgMXFSTYU+JfQ1a2rKsh8z3L0j8h8zVZpqVlHVuxYrGHZ4wxRa1cmXKMOGcEY+aNYdbmWWy8YyNpGWk0q96MMnHRPx+4MaVRbDzL0peQieRssgTXj8xXQ3b4cNax/svGGFOKPN33aX7b/rcAzNg4g5ZjW/LQrIfyOcoYEy7Rn5DFxWXVdMXHZyVkZcq4F2TVkGVkwMGDWcfu31/i4RpjTFEoE1eG0T1HAzB+4XjAJWbGmMgU/QlZfDxMngyjRsFZZ2X1IStXLqtMvXpw8qSbrf/QoaztHTuWfLzGGFNE6leuT2J8Igt3LQQgNS01zBEZY3IT/QlZXBw0awaPPeZqxNLTXfKVmJhVxn+2fl9C9uyz8NxzJR+vMcYUkfi4eKqXyxqctGrfKk6knwhjRMaY3ER/Qub/YHFfk+XJk5CQkLXdf3JYX0J24YXZa9GMMaYU2vPrHgBGdh/JyYyTzNk6J8wRGWOCif6EzH/KC19ClpaW1X8Msj8+ydeHrFq1korQGGOKzWuXv8bwTsN54MIHqF2xNk//8HS4QzLGBBH9CVkoNWT+s/X7asiqVi25GI0xppgMbT+UcZeOo3xCeW5qexMzfp5BekZ6uMMyxgSI/oTMv4asTBlXO5aWlj0hK1cOGjSAH36whMwYE7WaVWtGuqbzy9Ff2HZoGwB9/9uXh2Y9xM/7fw5zdMbEtuhPyHKrISsTMDnisGEwbRrMnQsVKmRP2IwxJgrUq+xaA95Y+gaNxzRm3E/jmLFxBqO/HU3zF5vz+YbPwxyhMbEr+hOy3PqQBSZct3iP1Zw+3WrHjDFRqV4ll5C9s/wdAJ78/knATY8BcNV7V/Hm0jfDE5wxMS76E7JQa8gaNsxK0ho3Lrn4jDGmhPgSr6V7lgKw5dAWKiRUYPOdm9l05ybKlinLq4teDWeIxsSs2EvI0tJydur37WvSxC23bFly8RljTAmpW6lujm19TutDQnwCTas1ZVDrQaz9ZW0YIjPGRH9CFtipP9i0Fz516rj3Fi1KJjZjjClBZcuUzbHt3u73Zi63qtWKfUf3WVJmTBiElJCJSD8RWSsiG0RkZJD9PUXkkIgs8V4PeNsbicg3IrJaRFaKyJ1+x4wWkR1+xwwouo/lJ5RpL3wyMty71ZAZY6Lcxjs28vHgj+nWqFvmtjNqnQFAq5dasWLvinCFZkxMClJNlJ2IxAMvAX2A7cBPIvKJqq4KKDpbVS8N2JYG3KOqi0SkMrBQRGb4HfsvVX2mkJ8hb7l16i+b85diZq1ZgwbFGpIxxoTLxN9MJD4unmbVm9GserNs+1rVapW5vHT3Us6qfVZJh2dMzAqlhqwLsEFVN6rqCWAScHkoJ1fVXaq6yFs+AqwGSjbbKUgN2fjxcPPN0KVLycVnjDEl6NYOt3Jzu5uD7jut+mkM7zQcgI0HNpZkWMbEvFASsgbANr/17QRPqrqJyFIRmS4iZwbuFJGmQAdgnt/mESKyTEQmikj1wGO844aJyAIRWbBv374QwvW88w60awciWdt8nfqDTXsB0KoVvPFG9gePG2NMjIiTOMZdOo5GVRqxfv/6cIdjTEwJJSGTINs0YH0R0ERV2wEvAlOznUCkEjAFuEtVD3ubxwGnA+2BXcCzwS6uquNVtbOqdk5KSgohXM+QIbBkSfZtvk79waa9MMYYA0DzGs35aM1H1rnfmBIUSkK2HWjkt94Q2OlfQFUPq2qKtzwNSBCRWgAikoBLxt5W1Q/9jtmjqumqmgG8imsaLV75NVkaY2JKfgOW/MqdIyLpIjLIW891wFI0qFe5HiknUhjwTvGMtTLG5BRKQvYT0EJEmolIIjAY+MS/gIjUFXFtgyLSxTtvsrdtArBaVZ8LOKae3+qVQPEP6fHv1G81ZMbENL8BS/2BNsAQEWmTS7kngS/8NvsGLLUGugJ/DnZsaTXinBEAmc+7NMYUv3wTMlVNA0bgbkargfdVdaWIDBeR4V6xQcAKEVkKvAAMVlUFugM3Ab2DTG/xlIgsF5FlQC/gL0X70YKwGjJjTJZQByzdjqvl3+vbEBEDlopRt0bdePyixzmZcZIjx4+EOxxjYkJI1UReM+S0gG2v+C2PBcYGOW4Owfugoao3FSjSouDfqd9qyIyJdcEGLJ3rX0BEGuBq8HsD5wQ7SS4Dlnz7hgHDABqXskeynVb9NAA2HdxE2zptwxyNMdEv+mfq9+ffqd9qyIyJdaEMWBoD3Kuq6UFPEHzAUtbJTnVQUgTwJWQ2/YUxJSO2qon8+5BZQmZMrMt3wBLQGZjkdZGtBQwQkTRVnZrbgKVoYQmZMSUrNhMym/bCGOM3YAnYgRuwdL1/AVXNnMpeRF4HPvWSsVwHLEWL6uWqUymxElsPbQ13KMbEhNhqsvTN2n/8uNWQGRPjQhywlJu8BixFBRGhbqW67Pl1T7hDMSYmxFY1kS8hs079xhjyH7AUsH2o33KuA5aiSZ2KddidsjvcYRgTE2Krhsw/CbMaMmOMyVPdSnXZk2I1ZMaUhNhKyPwfNG41ZMYYk6c6Feuw7fA2Plv3GYt3LQZg55GdzNueY4YPY0whxW5CZjVkxhiTp7qV6pJyIoVL372U6yZfB8DAdwbSdULXoBPG/uXzv9B9YveSDtOYqBC7CZnVkBljTJ7qVKqTubz54GZUlWV7lgHwydqsJ+h9tu4zdhzewZh5Y/hh2w8cSj1U4rEaU9rFbkJmNWTGGJOnGuVrZC6fzDjJkRNHqFm+JgBvLH0DgH/N/ReXvnspp71wWmbZeTusSdOYgoqthMw69RtjTMgaV3WPezq/8fkArP1lLfuO7qNq2arM2DiDhTsXMvYn99S8E+knMo+bu21uyQdrTCkXWwmZNVkaY0zIujTowvrb1/NQz4cA+HbLtwCM6TeGhLgEnp37LBsPbOTpPk8z5pIxfDf0O86ufTZzt1tCZkxBhZSQiUg/EVkrIhtEZGSQ/T1F5JDfBIkPeNsbicg3IrJaRFaKyJ1+x9QQkRkist57r150HysX1mRpjDEF0rxGc+pVrgfAv378FwBdG3blrNpn8e6KdwHoc1of7ux6J+c3OZ9uDbvx4/YfydCMPM+rqnyw8gOSjyYX7wcwppTINyETkXjgJaA/0AYYIiJtghSdrartvdfD3rY04B5VbQ10Bf7sd+xIYKaqtgBmeuvFy2rIjDGmwOpXrg+4KS9u63gbrWq1olO9ToAbiXl2nbMzy3Zr1I1Dxw+xet/qPM85Y+MMrp18LXd/eXfxBW5MKRJKDVkXYIOqblTVE8Ak4PJQTq6qu1R1kbd8BPd4kgbe7suBN7zlN4ArChD3qbEaMmOMKbDKiZUzl5/t+ywAp9c4HYBeTXsRJ1n/K+nWsBuQd8f+E+knuPerewF4a9lbfLg66p7NbkyBhZKQNQC2+a1vJyup8tdNRJaKyHQROTNwp4g0BToAvn+ldVR1F7jEDagd7OIiMkxEFojIgn379oUQbh78a8WshswYY0IiIow4ZwQTfjOBymVdcjbkrCGc1+g8Hr/o8Wxlm9doTmJ8Imt/WQvAyfSTTF8/nRPpJziYepC0jDQem/0YS3Yv4bXLX6Nz/c7c8OENHD15tMQ/lzGRJJSsJNjz2jRgfRHQRFVTvAfsTgVaZJ5ApBIwBbhLVQ8XJEBVHQ+MB+jcuXPgdQvGasiMMeaUvDjgxWzrTao14fvffp+jXHxcPKdVP411+9dxIv0E10+5nimrp9CzaU9W71vNifQTHEg9wDVtrmFo+6HUrVSX/m/354dtP3DxaReX1McxJuKEUkO2HWjkt94Q2OlfQFUPq2qKtzwNSBCRWgAikoBLxt5WVf966T0iUs8rUw/Ye8qfIlSWkBljTLFrWbMlU9dMpewjZZmyegq9m/Vm1uZZ7Pl1DwdSD5AQl8CDFz4IQPdG3YmXeGZtnpXveedtn8ecrXOKOXpjwiOUhOwnoIWINBORRGAw8Il/ARGpKyLiLXfxzpvsbZsArFbV5wLO+wlwi7d8C/DxqX+MEFmnfmOMKXbNqzfPtv6/If/LXD52/zG2372dM2u7ni2Vy1ama8OuvLH0Dfb9mtUtZdGuRRxPO57tPF0ndOX8185HtXCNJcZEonwTMlVNA0YAX+A65b+vqitFZLiIDPeKDQJWiMhS4AVgsLp/Md2Bm4DeflNiDPCOeQLoIyLrgT7eevGyGjJjjCl2ifGJAPRo3IOZN8+kQkIF1o1Yx9LhSylXphy1K2bvMvx8v+fZk7KHp394GoDp66fTaXwnhkwZQnpGeo7zv7n0Tf702Z+s35mJKiFVE3nNkNMCtr3itzwWGBvkuDkE74OGqiYDFxUk2EKzTv3GGFPsbj/3dpKPJfPcJc9RKbESAC1qtsi1fKf6nejRuAczNs7g6Mmj3PPlPVQpW4WP1nzEvV/dyzN9n8n2fMyhHw8FICEugef7P1+sn8WYkhK7M/VbDZkxxhSL+pXrM/6y8ZnJWCguanYRS3YvoeJjFVn9y2o+uOYDbm1/K8/Pe57Dxw+zcNdCwE1KW6N8DZpUbcK4BePYdmgbo74axe8+/l1xfRxjSkTsJmRWQ2aMMRHjsjMuA+CCJhfw+uWv0/f0vgxtP5S0jDRGfTWKi950DSqvDHyF5L8nM/PmmaRlpNH2lbY88f0TTFwykcPHCzSI/5QcOHaALzZ8wdvL3ranDJgiFVtZidWQGWNMRGpbpy0po1KomFgxc1u3ht2oWrYqLy94OXObb0La02uczqA2g/hg1QeZ+1btW0XXhl2LJT5VRUS44/M7eGvZWwD8/by/82SfJ4vleib2xG4NWcWKuZczxhhT4vyTMYCE+AT+3v3vAPRu1pu3r3o7WzPoYxc9Rvky5Xmk1yMArNy7ssDX/PXEr/k+d/Nk+kl6vNaD4Z8OZ8qqKZzf+HzqVqrLrC2zQr5OekY6Gw9s5MLXL+TuL+7mZPrJHGWmrZ/GVe9dla2mb8nuJaxLXpe5fij1EDd/dDObD24O+dqmdIitGjL/ZsqaNcMXhzHGmJCM6jGKDnU70KNxj8ynBPg0r9Gcw6MOEydxPDr7UVbsXZG5z1ejBS7pio+LZ/6O+ZxR8wzWJa+jS4MufLvlW66fcj2d6nfif0P+lzk61N+BYwe458t7+GHbD/yw7QcAnurzFJ+t+4zH5zzOkeNHcsTl7+jJo7ww7wVeX/I6a5Pd0wu+2/Idzao1o2aFmizcuZAHez7IloNbuPaDa/n15K/Un1mfW9vfyph5YzJr41LvT6VsmbK8ufRN/rvsv2w9tJWn+jxFvUr12H54O10bds38vB+u/pCx88dyVeurGNFlRCG+/ciyYf8G5mydwy9Hf+GmtjdRp1KdcIdUpKQ0zefSuXNnXbBgwamfYMECOOcct5yRARJ0AKgxJoKIyEJV7RzuOAqr0Pcvk6eer/dkztY5NKvejLNrn82MjTP423l/48a2N9JjYg92pezKVr55jeZs2L+BpApJ7Du6j8FnDaZnk55MWDyB0T1HM6DFAA6lHuK8ieexat8qBrQYQFKFJPqe3pfrz76e77d+T4/XenBug3N5tu+zHD15lGbVm9GkahOem/sclzS/hIe+fYipa6ZmXvOS0y/hL13/wtM/PM0P237gWNqxbDHVq1TP1QQufzvH5xveaTj/uOAfXPnelfy086cc+/s170eN8jXoUr8L9351L8fT3RxuA1sM5OzaZ7NkzxI61u3Igz0fDJp4Rrr/Lv0vt0y9BfUeFNSgcgPa1mlLv+b9uOPcOzLLHT15lK2HtpJ8NJm1yWsZ2GJgWBO3gty/YishW7wYOnZ0y6XocxsTyywhM6HYnbKbcT+N48cdP7Ji7wrKlynPpoObaFSlEfuP7efIiSMANK7amCPHj3Ag9QAta7ZkwW0LePmnlxk5c2TmuRpVacS838/jmR+e4bkfn+OLG7+g7+l9c1zz3eXvcv2H12fb1qFuBxbvXpxt28juI7mt022cVv00AJbuXkqHf3egdsXaXN36at5c9iY3nH0DI7qMoGm1pnQa34mkCklc3fpqdqfsJkMzeGbuM5nnu6/HfShKlwZdWJ+8nlEzR5Gu6STGJ3Ii/QQAi/+wmI/XfMyL818k+VgyZeLKkJaRxp/P+TMv9n8xszatNEjPSOeMsWdQtVxV3rnqHQ4fP8yI6SOYv2M+grDoD4toXas1K/auoN/b/fjl6C+Zx1ZKrETHeh25qtVV3Nn1zhKP3RKy3CxbBu3aueVS9LmNiWXFmZCJSD/geSAe+I+qBp2gWkTOAX4ErlPVyd62icClwF5VPSu/a1lCVrJmbZ5Frzd6AfDhtR/SoV4HGldtDLjalqEfD+WFfi9w+7m3o6pc9f5VLNi5gBf6vcBV71+VeZ7ezXoz8+aZuV7nvRXvsfXQVro27MotU29h08FNXHL6JXRp0IXujbrT9/S+QZOffy/4Nw2rNGRAiwEcTz9OuTLlMvelZ6QTH5fV51lVmb11Not2LaJdnXb0atYr27m2HdrGol2LGNBiAJ9v+JwqZatwYdMLM/cfTD1IxYSK3PvVvfzrx39xe5fbeb7f86UiKcvQDIb9bxgTFk/gg2s+YFCbQZn79v26j3avtGNXyi4S4xPJ0AzqV67PyO4jqZhYkVa1WvH0D08zedVkAG5tfytPXvwkNcrXyPb9FidLyHKzciWc5d03S9HnNiaWFVdCJiLxwDrck0K24x4TN0RVVwUpNwNIBSb6JWQXACnAm5aQRaZvNn1DuTLl6NaoW7btx9OO8/JPLzOs07DMgQQZmkFqWirly5Qn/uF4FKVz/c68ecWbtE5qHdL1Nh7YyKYDm+jdrHdEJjsZmsHfvvwbz/34HGXjy9KrWS9evexVGlZpmK2cqjJn6xxqlK+R+YiropZyIoWy8WVJiA8+48Hh44f542d/5J3l7wCulvGxix7L8b1u2L+BVxa8QnpGOkdPHuUv3f5Cq1qtclzrlqm38PGaj0nXdARhWKdhXNDkAqqUrcKlLS8FYNmeZVROrEyz6s2K7HNaQpabtWuhlfcfqhR9bmNiWTEmZN2A0ap6ibc+CkBVHw8odxdwEjgH+NSXkHn7mnrbLCGLIp9v+Jx3V7zLxN9MLLGalJKiqry66FWW7l7Kf5f9l4T4BN6+6m36Ne8HwN5f9/Lbj3/LZ+s/o0xcGZ7v9zxNqzVl++HtDGwxkAZVGpzSdVfuXcnulN1sO7yNKaun8Om6T6lRvgaXnH4JKSdSWLVvFe3qtuOJi56gQkIFHp39KOMWjKNptaZccvoljBs4rtBJ7vwd85m8ajI7j+zM1k/vj53/SNWyVXni+ycoV6YcM2+eyd5f93J+4/OpWaFwAwAtIcvNhg3QogUkJsLx4/mXN8aEXTEmZIOAfqr6e2/9JuBcVR3hV6YB8A7QG5iAJWQmiqzet5rrJl/H5oObGTdwHHUq1eG6yddx5PgR7jv/Pr7d8i2zNs/KLF++THmm3TCNnk17ZjvPnpQ9rE1eS9eGXTMHDKRlpHEw9SCVEisxfuF47vw8q/9W2fiy3HnunWw4sIGP13xMq1qtSKqYxPwd87M9n/S2jrcx/rLxxfLZF+1axNxtc7n7y7sz+90FipM4Rl84mvMancdXG7+iQZUG/L7j77M1L+enIPev2Jr2wjcPWbVqYQ3DGBMRgv3cDvyFOga4V1XTT+XXuYgMA4YBNG7cuMDHG1OcWie1ZvK1k7nw9Qu58aMbATgz6Uzm3DqH1kmtSU1L5a1lb1G3Ul1Oq34al75zKX/54i98c8s3pKalMnnVZKatn8YXP39BhmbQvm57rm1zLec1Oo/7v76fhbsW0qJGC5bvXQ7AjW1v5OrWV9Oveb/MpCZDM4gTNyXq8j3L+WjNR9QsXxNFuaXdLcX22TvW60jHeh3p1awX5cuUz2ymnLttLiv2rqBlzZa8MP8FHpj1AEDmoIiP1nzEJ4M/yTFnXlEIqYYsv46vItIT+BjY5G36UFUf9vYF7fgqIqOB24B93qb7vIeY56rQvzDXrIHWraFlS9d8aYyJeOFsshSRTWQlbrWAo8AwVZ3q7W+K1ZCZUi49I50HZz3IvB3zeG/Qe9QoXyNouUkrJjFkyhBqVajFsZPH+PXkrzSq0oib291M7Yq1eWHeC/x84GcAEuMTOTPpTJbtWcaoHqO449w7SKqYVJIfq9BS01J5Yd4LtElqQ6+mvZiyegp3TL+Db275hg71OoR0jiJtsgyl46uXkP1VVS8NcnzQjq9eQpaiqs8EHpObQt/Q9u2D2rXh2Wfh7rtP/TzGmBJTjAlZGdy97SJgB+7edr2qBp3uXURex5osTYybt30e102+jsplK/P+oPdpVatVZt8uVWXb4W08OOtBbmp7E72a9orIwQ2Fsf/Y/lwT1mCKusmyC7BBVTd6J58EXA6syvMoj6p+5920wi8pCY4ehXKht/8aY6KTqqaJyAjgC1zt/0RVXSkiw739r+R1vIi8C/QEaonIduBBVZ1QzGEbE1bnNjyXNSPWEC/xOUZIigiNqzbmtctfC1N0xa8gyVhBhZKQNQC2+a1vB84NUq6biCwFduJqy0J5qNgIEbkZWADco6oHQjimcMqXL/ZLGGNKB6+bxLSAbUETMVUdGrA+pPgiMyZyFaRTuwldKA8XD6Xj6yKgiaq2A14EpoZw3nHA6UB7YBfwbNCLiwwTkQUismDfvn3BihhjjDHGlGqhJGTbgUZ+6w1xtWCZVPWwqqZ4y9OABBGplddJVXWPqqaragbwKq5pNFi58araWVU7JyWVrg6BxhhjjDGhCCUh+wloISLNRCQRGAx84l9AROqK13NPRLp4503O66QiUs9v9UpgRUECN8YYY4yJFvn2IQux4+sg4I8ikgYcAwarN3wzj46vT4lIe1zz52bgD0X82YwxxhhjSoWQJobNr+Orqo4FxuZybNCOr6p6U+hhGmOMMcZEr1L16CQR2QdsCbF4LeCXYgznVEVqXBC5sUVqXBC5sUVqXFDw2JqoaqnvQBol9y+I3NgiNS6I3NgiNS6I3NiK7f5VqhKyghCRBcUxmWRhRWpcELmxRWpcELmxRWpcENmxRYpI/o4iNbZIjQsiN7ZIjQsiN7bijCuUTv3GGGOMMaYYWUJmjDHGGBNm0ZyQjQ93ALmI1LggcmOL1LggcmOL1LggsmOLFJH8HUVqbJEaF0RubJEaF0RubMUWV9T2ITPGGGOMKS2iuYbMGGOMMaZUiLqETET6ichaEdkgIiNL6JqbRWS5iCwRkQXethoiMkNE1nvv1f3Kj/LiWysil/ht7+SdZ4OIvOB7+kEBY5koIntFZIXftiKLRUTKish73vZ5ItK0kLGNFpEd3ne3REQGlHRsItJIRL4RkdUislJE7oyE7y2PuCLhOysnIvNFZKkX20OR8J1FA4nhe1gu94iI+JvKJbZI+LcYkfevfGIL6/cmkXr/UtWoeeGeJPAzcBqQCCwF2pTAdTcDtQK2PQWM9JZHAk96y228uMoCzbx4471984FuuAe6Twf6n0IsFwAdgRXFEQvwJ+AVb3kw8F4hYxsN/DVI2RKLDagHdPSWKwPrvOuH9XvLI65I+M4EqOQtJwDzgK7h/s5K+4sYv4dh96+ouX/lE1tYvzci9P4V9htQUb68L+ULv/VRwKgSuO5mct7M1gL1/P4o1waLCfdIqm5emTV+24cA/z7FeJqS/aZRZLH4ynjLZXAT5EkhYsvtH2aJx+Z3zo+BPpH0vQXEFVHfGVABWAScG2nfWWl7YfcwsPtXof7eidD7V0BsEfO9EUH3r2hrsmwAbPNb3+5tK24KfCkiC0VkmLetjqruAvDea+cTYwNvOXB7USjKWDKPUdU04BBQs5DxjRCRZV6TgK+KOCyxedXKHXC/mCLmewuICyLgOxOReBFZAuwFZqhqRH1npZTdw3KK9L+psP9b9InU+1eQ2CDM31sk3r+iLSEL1l9BS+C63VW1I9Af+LOIXJBH2dxiDEfspxJLUcc5DjgdaA/sAp4NV2wiUgmYAtylqofzKlqSsQWJKyK+M1VNV9X2QEOgi4iclUfxSPhbKw3sHha6SPibioh/ixC5969cYgv79xaJ969oS8i2A4381hsCO4v7oqq603vfC3wEdAH2iEg9AO99bz4xbveWA7cXhaKMJfMYESkDVAX2n2pgqrrH+4eRAbyK++5KPDYRScDdMN5W1Q+9zWH/3oLFFSnfmY+qHgRmAf2IgO+slLN7WE4R+zcVKf8WI/X+lVtskfK9ebEcJELuX9GWkP0EtBCRZiKSiOtI90lxXlBEKopIZd8y0BdY4V33Fq/YLbi2c7ztg70RGM2AFsB8r3r0iIh09UZp3Ox3TGEVZSz+5xoEfK1eI/mp8P3xe67EfXclGpt3ngnAalV9zm9XWL+33OKKkO8sSUSqecvlgYuBNUTw31opYfewnCL2bypC/i1G5P0rr9jC/b1F7P0r1I5vpeUFDMCN5PgZuL8ErncabvTFUmCl75q4tuKZwHrvvYbfMfd78a3FbxQS0Bn3h/kzMJZT6zT5Lq4K+CQuQ/9dUcYClAM+ADbgRpecVsjY/gssB5Z5f8D1Sjo2oAeuKnkZsMR7DQj395ZHXJHwnbUFFnsxrAAeKOq/+8L8rZXmFzF8D8PuX1Fz/8ontrB+b0To/ctm6jfGGGOMCbNoa7I0xhhjjCl1LCEzxhhjjAkzS8iMMcYYY8LMEjJjjDHGmDCzhMwYY4wxJswsITPGGGOMCTNLyIwxxhhjwswSMmOMMcaYMPt/5ZaUeeBzfMQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Fi2DXLujVC/btc48+ysuECa51bPjwoo8vWESsFpkxQeYbN2YJmTHRw1rIcjJ9untuZI8e0KoVrF7tZhvmRNVV42/VCs49N2hhBkW9ei4hW7/eFaz97rtQR2RMRLMWMmOijyVkOZk2Dc4+2xVrbdXKPWNyxYqct581y7Wi3X13/mdWFneJie6ZnO3awccfw1VXwY4doY7KmIhlCZkx0ccSsuzs3++6LHv0cN9btXLvuY0je+45l7z171/k4QVdYqKbPVqtGkyeDHv2wA03uCTVGFPoLCEzJvpYQpad+fNdF2THju5748bu4d45jSPbsAE+/RRuvRVKlQpenMEyYIArVDt3Llx+OYwe7bp0A3lgujEm3ywhMyb6BJSQiUhPEVktIutE5IQR6yJSUUQ+FpGlIrJARFr4rRsqIstEZLmIDMuy313ecZeLyKgCX01hmTvXdTuefbb7HhsLzZvn3EL2+utu+9tvD16MwVS3rnu+ZoUK7vttt0G3bi4hs0cqGVPoLCEzJvrkmZCJSCzwAtALaAb0E5FmWTZ7GPhZVVsBA4DnvX1bALcA7YDWQG8RSfLWnQf0AVqpanPgmUK5osIwd65LwE45JWNZq1bZJ2RpafDOO9C9O9SpE7wYQ0kErrnGlcJYvjzU0RgTcdILwx63wrDGRItAWsjaAetUdYOqpgATcYmUv2bATABVXQXUF5HqQFNgnqoeVtXjwGzgcm+f24ERqnrU2y/4o8RfeeXEbsi0NNdl2b595uWtWrmB7L//nnn5rFluBuINNxRlpMXPxRe7988/D20cxkQgayEzJvoEkpDVBrb4fd/qLfO3BLgCQETaAfWAOsAyoIuIVBaR0sBFQF1vnyZAZxGZLyKzReSs7E4uIoNFZJGILNq5c2eg15W3Y8dc19sLL2RevmaNG7TeoUPm5aef7t5//DHz8jffhPLloU/WHDXC1a4NbdrAZ58V7DhLlrif3Zw5hROXMRHAEjJjok8gCVl2NRyyDhwaAVQUkZ+Bu4CfgOOquhIYCXwJfIFL3I57+8QBFYH2wP3AJJET60Wo6jhVbauqbasW5sOtt21zrWFZC57OnevesyZkbdu6umTz5mUsO3AAPvoIrr46Mgfz5+Xii+GHH2D37vzvqwovvujG6U2dChddlPGzz86GDVZqw0QNS8iMiT6BJGRbyWjVAtfy9av/Bqq6X1VvVNXTcWPIqgIbvXWvqeoZqtoF2A2s9TvuZHUWAGlAlYJcTL74HgWU9ZFAc+e6weunnpp5edmy0LJl5oTso4/g8GEYOLBIQy22evd2Se0XX+RvvwMH4NprYcgQOO8810pWs6Z7KkLWFshjx+Dxx6FJExg0qPBiN6YYS4i1Sv3GRJtAErKFQJKINBCReOBaYKr/BiJSwVsHcDMwR1X3e+uqee+JuG7N97ztpgDdvHVNgHjgjwJdTX74WsY2b848U3DuXDd+LCabH0379m58ma/+1nvvQaNGkfPcyvw66yyoWjV/48hWrHD7ffghjBjh9m3VCmbOdInwBRfATz+5bdeudaVHHnvM1XibPds9Y9SYCGctZMZEnzwTMm8w/p3ADGAlMElVl4vIbSJym7dZU2C5iKzCzcYc6neIj0RkBfApMERV93jLXwcaisgy3ESBgapBrKHgaxk7eNCNGQP3zMrly0/srvRp395ts3o17N0LX38NfftGXmX+QMXEuK7G6dPh+PG8t5882VX79/3sHnwwI/FNTIRvvoFy5eD88+Hpp90YtXXrYNIkV3j3wAHXmmZMhLOEzJjoE1AdMlWdpqpNVLWRqj7tLRurqmO9z3NVNUlVT1PVK/ySLlS1s6o2U9XWqjrTb3mKql6nqi28Ls2vC/vicuU/dsyXnC1a5FrLss6w9PEtnzfPPVrp+HFXKDWa9e7tEtrvv895m7Q0+PvfXfLasqXrluza9cTtGjRws1bLlYO//c21pC1d6h7V1Lmz26aoB/+rwvjxLpZHHinac0WCVatc2Ze9ezOWHTrknnbhLy0Nvv0Wbrkl6F3PAdRRFBH5j7d+qYickde+InK6iMwTkZ+9SUftCjNmS8iMiT7RW6k/ORkS3DiN9OTMV2esTZvs92nSxHWrzZvnnulYs6Zr8YlmF17ofo5TpmS//tAhuPJKV1j2pptcwlWrVs7Ha9DAJXcTJsBXX2XUdqtTx6379tvCvoIMP/4InTrBdde5SR9vvmmFb7Nz6BC88YbrTm7a1D3JoX59l8AOGOAesVWjBgwb5rr4H33UPe2iSxfXzR8bG7Sfa4B1FHsBSd5rMPBSAPuOAh73xs3+w/teaCwhMyb6RG9CtnlzRiV+XwvZihVQpYobF5WdmBi3z6xZrpuuT5/sx5pFE18X4yefnPif7LZtrmXrk0/c45ZefTUjCc5NnTrQr5/7j9tf584uISvIf+YrV7onKvh3fe7Z4yYYtG3rukhfew3GjoVff4Wffz75c0Wan35ypWJq1nTJ9a5dMGqU+/fQrRv885/uz/r6613h4DFjXKvyk0+6sZbvvOPq+I0bF8xu/kDqKPYB3vYmGM0DKohIzTz2VcBXObo8WSY6FVRcTBxgCZkx0SQu1AGEhKpLwnr2hIULM1rIli93Ffpzc/bZMGOG+3zZZUUaZti47DLXhbtsmeuSBPez7NnTdWVNnZpRSLYgOneGt992Y/hOOy1/+x496iYR/POfkJICb70FL7/sEoN773XJxV13uRmdFSq4xEHE1VnLqcU0Ghw+DBMnugR14UL3TNerr3Zdjx07ZiRWXbu6BLxSpYwSMI8+6sYKdu/uHr8VGtnVUTw7gG1q57HvMGCGiDyD+8U225k9IjIY1+pGYmJiwEGLCPGx8RxNtUr9xkSL6Gze2bULjhxx3SyJiS45Uw0sIfONIytf3pVsMHDJJe4/Zl+35ezZ7j/r1FTXolUYyRi4Li/If7flwoVw5plutmbfvq5rul071712/fWuK3TxYvdsTt/zOqtXd9sUtPBtuFq7Fu65xxUAHjTIdVP+5z+u1fCtt1zXbtZWrtq1M9fjq1/ftaSFLhmDwOoo5rRNbvveDtyjqnWBe4DXsjt5QeooxsfGWwuZMVEkOhMyXxdlYqJ7bd7s/qPZvz+wFjJwSUZ8fO7bRosaNVyi+sknLinr0cONE5s7N+MJB4UhKcmNT8ouITt0yHWnNW+eUcvs6FF46CEX2969LrmaMMG14n31lZvJOW6cK26bXZy9e8OCBSc+Liur7793j87yr1EXjtLSXEtnr15uvOSYMW6M4OzZrvXzrrugYsVQR5lfedZRzGWb3PYdCEz2Pn+A694sVJaQGRNdojMh83VR1qvnXv4PyW6WdbxvFpUquVl4TzxRtDGGmz59XCtT376ui++779zPtjCJuG7LWbNct6PPwoXunOPGuWr+nTrB//2fm6U5YoRLlpYvz9xSFxcHDz/sut6yjlXz6d3bvU+bBhs3ukHr69ZlrE9OdgVuO3VyrUYdO8L997vW1+LqwAFXQqRVKzfOa+VKV/plzBjXDXzxxW583WOPuX8nEye6lsnwLe2SZx1F7/sAb7Zle2Cfqm7PY99fAd9U4W5kFLwuNAmxCZaQGRNNVDVsXmeeeaYWitGjVUF1507VJ55wn//1L/e+Y0fhnCParF6tGhur2r276oEDRXeeDz5wf05du7o/v1GjVOPiVOvWVZ01S/W331Q7dXLb1Kih+tlnJ3+utDTV2rVVGzRQLVnSHbN0adUxY1Qff1y1VCn3evRR1V9/VR082G2TlORiKU62bVN94AHV8uVdjGedpVq2rGpMjGq5cm7Z2WerTpigevRoqKPNBFikBbhv4J6huwZYDzziLbsNuM37LLjZlOuBX4C2ue3rLe8ELMY9Dm4+cGZeceT3/lVvdD0d+PHAk/65GWNCLz/3r5AnWfl5FVpCNmyY+481LU31zTcz/oOvWrVwjh+t1q9XTUkp+vOMH68aH+/+DEG1b1/V3bsz1h89qvruu6p//FHwcw0Z4s5x9dWq8+er9ujhvvuWJSdn3v6rr1QbNnTrb7klI66UFJfs/PBDwWPKj1WrVG+6SbVECZd8XX216oIFbt2OHaoPPqh6ww2qc+cGN658KGhCVlxe+b1/Jf0nSft92C9f+xhjipf83L+ic5bl5s1u7JhIRrfa99+7ridz8ho2DM55+vd3f2533+26HG+9NXOXWnw8/OUvhXOuf/3LHd83e/SLL1w3Xu3aGZMM/J1/Pvzyi5thOHq0G1c3dKjr0lyzxm0zYIArF1G9euHEmJ0ff3QzSidPdqVGBg92s0n9/4yqVnVduqZYsjFkxkSX6EzIkpMzEjHfVPTjx/MeP2aKj44d3Zi1olauXEYyBi7x69cv931Kl4Z//9slhbfe6saeNW3qigkvXOjWffedS9ByGr92subOdXW/pk93M4EfesglhNWqFe55TJGzhMyY6BKdCdnmzXCG93SUOnXcf7Kqec+wNCY/Tj/dzeBctsz93YqLczXbWrZ0Sd3s2a6gamH4/ns3EP+rr1xx46efdsVuy5cvnOOboLOEzJjoEn2zLA8fhp07M1rI4uNd5XGwhMwUvthYaN3aJWM+ffq4lrcJE/J3rO3b3dMk/M2b58qMdOrk6qs98wxs2uRmkFoyFtasMKwx0SX6ErItXuFt/6rZvuTMEjITDKVKuYfSf/ihq5WWl127XDmNBg3c39FLL3VPP+jdGzp0cI93euYZV5rjr3+FMmWK/BJM0bMWMmOiS+QnZG3auArsPr4aZP4JWcOGrrhplSrBjc1Er379YN8+N0kgJ0eOuEH3jRq5umrXXOPGh82Z41rZfvjBTTrYsMElYqVLBy9+U+QsITMmukT+GLJVqzI/SPqPP9y7/yDnf/7TFRQ1JljOP9/NcpwwwRVkHTnSjWe87z4oWxbefddNBti61bWE/etf0KKF2/eOO9wzIi+4IONRTybiWEJmTHSJ/IQsJQV278747vtcqVLGMt8jlIwJlhIl4Kqr4JVXXGmK+Hg3vvGll1xJjSVLoG1beOcdOPfczPtWqgRXXhmSsE3wJMRZpX5joklkd1mmprrn8/knZLt2uXf/hMyYUBg0yA32v+EG1+24cKGbmZmS4lrI5s8/MRkzUcNayIyJLpHdQuZ73qEvCQOXnJUr51oojAmlM85wD0X3FbWtXh2+/DK0MZliIz7GEjJjoklkt5D5ErKsXZbWOmaKi/B9aLcpYtZCZkx0iZ6ETNV93rULKlcOXUzGGBMAS8iMiS7RkZClpLiuIbAWMmNMWLCEzJjoEh0JGWR0W1pCZowJA/Gx8Rw9bpX6jYkWkZ2Q+VdB9yVk1mVpjAkD8bHxpGoqqWmpoQ7FGBMEkZ2Q+beQ7drlSmDs2WMtZMaYYi8+Nh6AY2nHQhyJMSYYoich270b9u93SZklZMaYYs6XkNk4MmOiQ3QlZL5uS+uyNMYUcwlxCYAlZMZEi+hJyHbtsir9xpiwYS1kxkSX6EnI/FvILCEzxhRz/glZaloq45eOtwH+xkQwS8iMMaYY8k/I5iTP4bqPr2N28uwQR2WMKSrRkZDFxGTusrQxZMaYYs4/IdtxaAcAOw/tDGVIxpgiFFBCJiI9RWS1iKwTkeHZrK8oIh+LyFIRWSAiLfzWDRWRZSKyXESGZbPvfSKiIlKlQFeSHV9CVr165hayihUL/VTGGFOY/BOy3Ufcvcv3boyJPHkmZCISC7wA9AKaAf1EpFmWzR4GflbVVsAA4Hlv3xbALUA7oDXQW0SS/I5dF+gObC74pWTDl5DVqJGRkJUrByVKFMnpjDGmsPgSsqPHj7LriGvd970bYyJPIC1k7YB1qrpBVVOAiUCfLNs0A2YCqOoqoL6IVAeaAvNU9bCqHgdmA5f77TcaeADQgl1GDnyV+mvWdMmYVek3xoQJayEzJroEkpDVBrb4fd/qLfO3BLgCQETaAfWAOsAyoIuIVBaR0sBFQF1vu0uBbaq6JLeTi8hgEVkkIot27szn+An/FjLfGDIb0G+MCQOWkBkTXQJJyCSbZVlbtEYAFUXkZ+Au4CfguKquBEYCXwJf4BK3415y9gjwj7xOrqrjVLWtqratWrVqAOH68SVkNWvCsWOwZYslZMaYsJAQm1EY1rosjYl8gSRkW/FatTx1gF/9N1DV/ap6o6qejhtDVhXY6K17TVXPUNUuwG5gLdAIaAAsEZFN3jF/FJEaBbucLPwTMoB166zL0hgTFqyFzJjoEhfANguBJBFpAGwDrgX6+28gIhWAw94Ys5uBOaq631tXTVV3iEgirluzg6ruAar57b8JaKuqfxT8kvz4d1kC/PmntZAZY8KCJWTGRJc8EzJVPS4idwIzgFjgdVVdLiK3eevH4gbvvy0iqcAKYJDfIT4SkcrAMWCIl4wFR0qKq0Hm39VpCZkxJgz4J2S7Dntdloety9KYSBVICxmqOg2YlmXZWL/Pc4GkrPt56zoHcPz6gcSRbykpEB+fuZvSuiyNiSoi0hNXiicWeFVVR2RZL976i4DDwA2q+mNe+4rIXcCdwHHgc1V9oDDjTi97kXo0UwuZquJCNsZEksiv1B8fn7lVzFrIjIkaAdZR7IX7hTIJGAy8lNe+InIervxPK1VtDjxT2LH7ErJdh3eRqqnULFuTVE3lQMqBwj6VMaYYiI6EzL8yvyVkxkSTQOoo9gHeVmceUEFEauax7+3ACFU9CqCqOwo7cF9Ctv3gdgCSKrtOCBtHZkxkiuyE7OhRl5CVLAmlS7tl1mVpTDQJpI5iTtvktm8ToLOIzBeR2SJyVnYnL0gdxawJWeOKjQEbR2ZMpIrshMzXQgYZiZi1kBkTTQKpo5jTNrntGwdUBNoD9wOTJJuBXQWpo+hLyH47+BtgLWTGRLroSch8iZglZMZEkzzrKOayTW77bgUme92cC4A0oEohxk1cjJtztf2A12VZyRIyYyJZ9CVk/uPJjDGRLr2OoojE4+ooTs2yzVRggDjtgX2quj2PfacA3QBEpAkQDxRqHUURISE2Ib2FrHElr8vSqvUbE5ECKnsRtlJSIME9foTKleGUU6BEidDGZIwJmgDrKE7DlbxYhyt7cWNu+3qHfh14XUSWASnAQFXN2hVaYPGx8emzKhtVagRYC5kxkSryEzJfC1nHju55lsaYqBJAHUUFhgS6r7c8BbiucCM9kW8cWbn4cpSNL0uZEmUsITMmQkVPl+WwYTBlSiijMcaYfPElZJVKuSEXlUtXti5LYyJU9CRkxhgTZrImZJVKVbIWMmMilCVkxhhTTPkSssqlXdkeS8iMiVyWkBljTDF1QpdlqcpWGNaYCBXZCZmvUr8xxoSh9ISspHVZGhPpIjshsxYyY0wYy2kMWRFU2DDGhJglZMYYU0wlxLk6ir4xZJVLVSZVU9NrkxljIoclZMYYU0xl10IG9oBxYyJR5Cdkvkr9xhgTZnJKyGwcmTGRJ/ITMmshM8aEqfSyF6Uyyl6AJWTGRCJLyIwxppjKrlI/2APGTfEwZdUUvlj3Rfokk52HdvLWz2/x28HfQhxZeIrcZ1mmpkJamiVkxpiwZV2Wprjac2QP13x4DSmpKfRo1IP2tdszet5oDqQcoGx8WYZ3HM49He6hdInSoQ41bERuC1lKinu3hMwYE6biYywhM8XT5JWTSUlNYejZQ1mwbQFPzHmCbg26MeO6GXRv2J2/ffM3mvy3Ca//9DqpaamhDjcsWEJmjDHFVEJcAuXiy1EitgTgWszKxpfNNMty877NtHulHdv2bwtVmCYKvbfsPRpXaszoC0ez/u71rL5zNVOunUKPRj2YfM1kZt8wm9qn1GbQ1EG0Htuaqaunoqp8vuZzurzRhf4f9WfVH6tCfRnFSuQmZEePundLyIwxYer2trfzcu+XMy2rWbYm2w5kJF/fb/6ehb8uZNamWUGOzkSr7Qe28/XGr+nfoj8iQqVSlWhSuUmmbbrU68K8QfOYdOUkUlJT6DOxD7WfrU3v93qzZf8Wpq6eSvMXmzNwykDW714foispXiI3IbMWMmNMmGtZvSX9WvbLtKxehXps3rc5/XvyvmQAlu9cHtTYTPSatHwSip7wdzMrEeGq5lex/I7ljOs9jmZVm/HSxS+x5s41bBy6kWFnD2PS8kmcOuZUBn0yiA17NgTpCoonS8iMMSaMJJ6SmJ6EAenJmSVkJlgmLJtAmxptOK3KaQFtXyK2BLeceQtfDfiK29reRonYElQtU5X/u/D/2HD3Bu5sdyfjfxlPk/824cZPbmTtrrVFfAXFU+QnZFYY1hgTQepVqMdvB3/j6HE3LMOXnK3YuSKUYZkItG3/Nm777DYemfkIe//cS5qmMW7xOBZsW0D/lv0L5Rw1y9XkuZ7PsXHoRu5qdxcTl03ktBdOo99H/fjl918K5RzhInLLXlgLmTEmAiWWTwRgy/4tNK7UOL2FbP3u9Rw5doRSJUqFMjwToKW/LyUhNoFTq5wa6lBOkJqWyosLX+SRrx8hJTWFlNQUXl78MvUq1OPH7T/SObEzg9oMKtRz1ixXk9E9RzO803BGzxvNCwtfYOKyifRu0pvhHYfTMbFjoZ6vOIr8FjJLyIwxEaRe+XqA66pUVZL3JlOzbE0UtVlrYeLNn9+k7bi2tB7bmjELxqQXVi1se//cS99JfXlnyTuoKnuO7OH6j6+nwfMNeHfpu9med9mOZXR8vSN3f3E359Q9hxVDVrB48GJOr3E6u4/s5q3L3mL2DbOpWKpikcRcvWx1RlwwguRhyTxx7hPM3TKXTm90otPrnfhk1SekaVr6tqlpqaz6Y1WmZeHMEjJjjAkjvhay5L3J7Du6jwMpB+jVuBdg48gK4pXFr/D0nKeL/D/3v3/9d2785Ea61u/K+Q3P567pd3H5+5fzx+E/ANhxaAc93+1J30l92X5ge4HO9cmqT5i8cjIDpgyg8xudafFSCyYum0ipuFJc//H1dH6jM4t/XQxASmoKj37zKG1ebsP6PesZf8V4pv9lOg0rNqRNzTZ8NeArNg7dyIDWAxCRAv8c8lKpVCX+3vXvJA9L5vmez7N1/1Yue/8ymr7QlLGLxvLB8g9oNbYVTV9oyqljTmXMgjEcTDlY5HEVJUvIjDEmjNQ5pQ6CsHnfZpL3uvFj5zc8n7iYOBtHdpKOpx1n+Mzh/O2bvzFwykCOpR4rkvP88vsvPPXtUwxsPZBp/afxWb/PeLbHs0xfN51WL7Vi7KKxtB3XljnJc5i2dhotXmrBpOWTTvp8n639jFrlavHKJa+w6o9VVChZgXmD5rHsjmW8dulrrNm1hrNeOYvrP76es145iyfmPME1za9h5ZCV9G/ZPyiJV17KxJfh7rPvZt3d63iv73ucknAKt39+O1d/eDWpaamMvGAkVUpX4a7pd1H72drc88U9YVtGI6CETER6ishqEVknIsOzWV9RRD4WkaUiskBEWvitGyoiy0RkuYgM81v+bxFZ5e3zsYhUKIwLSmcJmTEmAiXEJVCjbA2S9yWnjx9rXKkxTSo3CaiF7MnZT9L1za5FHWZY+W7zd+w+spuejXvy7tJ3ufz9yzl87HChn2d28mwAHj/3cUrElkBEuKfDPSy4eQEVS1Xk9s9vd/Hc9B0/3foTjSs15poPr+HKSVfy+8HfMx1LVdl/dH+O50pJTWHGuhn0TurNzWfczJZ7trD0tqWcWetMYiSGm9rcxNq71nL/Ofczafkkdh7aydRrp/LuFe9SpXSVQr/2goqLiePaFtey4OYFfHvjt3x8zccsu2MZD3R8gLmD5jJ30FwuTrqYMQvHkPTfJC4afxHT1k4Lq6cE5JmQiUgs8ALQC2gG9BORZlk2exj4WVVbAQOA5719WwC3AO2A1kBvEUny9vkSaOHtswZ4qOCX48cKwxpjIpSvFplvhmVi+USaV23O8h15J2Qfr/qYOclzWLlzZVGHGTY+WfUJCbEJfHDVB4y9eCzT1k6j21vd2HloZ6GeZ07yHOqeUpd6FeplWt66RmsW3bKIVy95lUWDF3FGzTM4rcppfH/T94w4fwSfrfmMZi82Sx8LtvPQTnq824Oq/67K47Me58/jf55wrm+Tv+VAygF6N+kNQKkSpYiNic20TfmS5RnZfSSbhm5i9Z2rueTUSwr1eouCiNApsROXnXYZcTEZ8xLb12nPhL4TSB6WzD+6/oOffvuJiydcTNJ/kxj53chC/7MsCoG0kLUD1qnqBlVNASYCfbJs0wyYCaCqq4D6IlIdaArMU9XDqnocmA1c7m33P28ZwDygToGvxp+1kBljIlRi+cT0FrKE2ASqlalG86rN2bBnQ64tO4ePHWbp70sBl5gZ19I0ZfUULmh4AWXjy3Jr21uZfM1klvy+hHNeP6fQamKpKt9u/pbO9Tpnu75UiVIMOmMQ1cpUS18WFxPHg50e5Kdbf+LUyqcyYMoAur/TnTPHncm3yd9yXv3zeGz2Y7R6qRX/W/+/TMf7bM1nJMQm0K1Btzxjq1muJuUSyhXsAouJWuVq8di5j5E8LJmJfSeSWD6R4TOHU/vZ2lz74bV8s/GbIptEUVCBJGS1gS1+37d6y/wtAa4AEJF2QD1cgrUM6CIilUWkNHARUDebc9wETM/u5CIyWEQWiciinTvzkeFaQmaMiVD1ytdjy74tbNq7ibrl6xIjMTSv1jzPmZaLf11MqqaSEJvAlFVTghdwMfbLjl/YtHcTfU7NaGe47LTL+HrA1+w5soezXz27UB5LtX7Pen47+BudE7NPyHLTtGpTvrvpO8b0GsOCbQuIkRh+GPQDX1z3BTOum4GiXPjuhVw56cr02befrvmUbg26USa+TIFjD0fxsfFc0+IaZt0wixV3rGDIWUOYsX4G3d7uRpMxTRjx3Yj0SRP7j+7nX9/+i6HThzJv6zz+PP4nLy58kRYvtqDnuz1575f3OHLsSJHHHEhClt2ovqzp5Qigooj8DNwF/AQcV9WVwEhc9+QXuMTtuP+OIvKIt2x8didX1XGq2lZV21atWjWAcD2WkBljIlRi+USOph5l0a+L0stgNKvqRpLkNrB/3tZ5AAw5awgLf13I1v1biz7YYm7KqikIckJ3XYe6HZh/83xqlK1B93e68+qPrxboPN8mfwtwUgkZQIzEMKTdEDYN28TyO5ZzRs0zAOjRqAe/3P4LT533FNPWTuO0Madx1/S7WL9nfXp3ZbRrWrUpo3uO5td7f+Wdy9+hVrlaPDTzIeqOrkuPd3pQ/7n6PPz1w7y8+GU6vNaBiiMrMmTaEEqXKM3KP1bSf3J/avxfDQZ9MojZm2YX2UzcQBKyrWRu1aoD/Oq/garuV9UbVfV03BiyqsBGb91rqnqGqnYBdgPp7b8iMhDoDfxFC7sN0Sr1G2MilC8J27h3Y/rnpEpJlIgpwbIdy3Lcb962eTSq2IjBZw4G3NipaPfJ6k9oX6c9NcrWOGFdo0qNmDtoLt0adOOWT29hyOdD8pyB+eP2H2n6QlMem/UYx9My2h/mbJ5D5VKVaVq1aYHirVSq0gmtXiXjSvJIl0dYOWQll5x6CS8sfAGAi5MuLtC5Ik2pEqW4rtV1zL5hNqvvXM3959zP+j3r6ZTYiYW3LOT3+37nlUteoX+L/swcMJP5N89n49CNzBwwkyuaXsGkFZM4961zWbBtQZHEF0hCthBIEpEGIhIPXAtM9d9ARCp46wBuBuao6n5vXTXvPRHXrfme970n8CBwqaoW/nQWayEzxkQoXy0y/88lYkvQsnrLHP+zUFXmbplL+zrtObXKqZxW5bSoH0e2Zd8Wftz+Y6buyqzKlyzP5/0/574O9/Hiohe54J0L+O3gb9lu++P2H7ng7QvYtn8bj89+nK5vdmXT3k2AayHrlNiJGCm6alP1KtTj/SvfZ/YNs3nrsrdOmDxgMjSp3IR/XfAv1t+9nqn9ptK2VlvKlyzPzWfczGt9XqNbg26ICDESQ7cG3Xijzxv89tff+OCqDzi79tlFElOefzO8gfd3AjOAlcAkVV0uIreJyG3eZk2B5SKyCjcbc6jfIT4SkRXAp8AQVd3jLR8DlAO+FJGfRWRs4VySxxIyY0yE8v+P1v9zhzodWLBtQaaWGZ+t+7ey/eB22tdpD8Dlp13OrE2z2H1kd9EHXEx9vvZzgDxnF8bFxPHvHv9m/BXjWbhtIW1ebpPeBenz0/afuODtCzgl4RSW3r6U8VeMZ9mOZbR6qRXP/PAM6/esP+nuyvzqUq8LA1oPCMq5okmZ+DJc2ezKIqvPFlCqrqrTVLWJqjZS1ae9ZWNVdaz3ea6qJqnqaap6hV/Shap2VtVmqtpaVWf6LW+sqnVV9XTvdduJZy4AS8iMMQRUR1FE5D/e+qUickY+9r1PRFREglq4qXxCecrFu1lx/q1lHep04NCxQ9l2W/rGj/kSsr5N+5KqqXy44sMgRFw8fb72cxpUaEDTKoF1I/Zv2Z/5N8+nXHw5znvrPEZ8N4I0TWP5juV0f6c75RLKMeuGWdSvUJ/+Lfuz5LYltKnZhvu/vB8gxxmWxoBV6jfGRLAA6yj2ApK812DgpUD2FZG6QHdgcxFfxglEJL1lzDeGDNxAdIC5W+aesM+8rfMoGVeSVtVbAXBGzTNoVrUZb/78ZtEHXAwdOXaEmRtmcnHSxflq8WhZvSWLBi+ib7O+PDTzIXq804Pz3z6f+Nh4vh7wNfUr1E/ftn6F+nw94Gue6f4MVzW7ijY12hTBlZhIEdkJWUwMxMbmva0xJlIFUkexD/C2OvOACiJSM4B9RwMPcOKs86DwtYzVOSWjhGODCg2oVqYac7dmk5Btm0fbWm2Jj3W/pIoIA1sPZO7WuazZtSY4QRcj32z6hiPHj5zUTMRTEk5hYt+JvNz7Zb7f8j1pmsbMATNpVKnRCdvGxsTy13P+yqSrJlEitkRhhG4iVOQmZEePWuuYMSaQOoo5bZPjviJyKbBNVZfkdvKTrqMYgDNrnknLai1JiMuYSS4idKjT4YSE7HjacX7c/iPtarXLtPy6VtcRIzG8veTtQo0tHHy25jNKlyhN1/on9xgpEWHwmYNZOWQlP976Y4FnTxoTuQlZSoolZMaYQOoo5rRNtsu9ItePAP/I6+QnXUcxAI92fZSFtyw8YXmHOh1Yt3tdpkfFrNu9jj+P/0nrGq0zbVurXC26N+zOO0vfKbLaSsWRqvL52s/p3rA7JeNKFuhY9SvUz9RKaczJsoTMGBPJ8qyjmMs2OS1vBDQAlojIJm/5jyJyYiGrIhQbE5updczHN45s/rb56ct8j0vyjR/zN7D1QDbv21wo1ejDxbIdy9i8b7PV6TLFSmQnZFYU1phol2cdRe/7AG+2ZXtgn6puz2lfVf1FVaupan1VrY9L3M5Q1eyLUwVZ21ptiYuJyzSwf+nvS4mV2GxnE1522mWUTyjPuMXjghlmUB09fjT9s6ry5JwniZVYLm5iCZkpPiI7IbMWMmOiWoB1FKcBG4B1wCvAHbntG+RLyLfSJUrTunrrTOPIlv6+lNOqnJZti1qpEqUY1GYQH674MCIfpXQo5RC1n63NFe9fwcGUg4xbPI4PVnzA092epla5WqEOz5h0lpAZYyJaAHUUVVWHeOtbquqi3PbN5vj1VfWP4FxNYDrW7ci8rfPSH4i89PeltKzeMsft72x3J4ry4sIXgxVi0Gzcu5FdR3bx8aqP6fBaB4bNGEaPRj24v+P9oQ7NmEwsITPGmAhzYeMLOXL8CHOS57Dvz30k70umVbUTx4/5NKjYgEtPvZRxi8elJ3GRInlvMuAmQWzet5kKJSvw9mVvF+kjjIw5GZH7N9ISMmNMlDq3/rmUjCvJ9HXT06v2Zzeg39/Qs4ey68guxv8yPhghBs3mfa5u7+AzB7PijhUsuHkB1ctWD3FUxpzIEjJjjIkwpUuU5tz65zJ93fT0GZa5dVkCdK3XlVbVW/HcvOciqgTG5n2bKRFTghpla1D7lNrULV83752MCQFLyIwxJgL1atyLNbvWMGX1FMonlKfuKbknIiLCgx0fZPnO5UxeOTlIURa95H3J1C1f17ooTbEXuX9DrVK/MSaK9WrcC4D/rf8fraq3Cuh5jdc0v4ZTK5/K47Mfj5hWss37Nmd6ALsxxVXkJmTWQmaMiWJJlZNoXKkxkPf4MZ/YmFj+0fUfLNuxLGJayTbv25zpAezGFFeWkBljTITytZK1rJb7+DF/1zS/htOqnHZSrWTH047z/ebvUQ3J89ZPcCz1GNsObLMWMhMWIjshs0r9xpgo1rdpX2IkJv1xSoGIjYnlH11cK9mEXybk63xTVk2h0xudeG7ec/mMtGj8euBX0jTNEjITFiI7IbMWMmNMFOtavys7798ZcJelzzUtrqFtrbYM/2o4h1IOBbzfip0rALj/y/uZvWl2vs5ZFHwlL6zL0oQDS8iMMSaCVSpVKd/7xEgMz134HNsObGPU96MC3m/t7rVUL1OdpMpJXP3h1SF/FFPyPlcU1lrITDiwhMwYY8wJOiZ25NoW1zLqh1HpLU15Wbd7Hc2rNWfy1ZM5fOwwl753KQdTDhZxpDnzxW21x0w4sITMGGNMtkZeMBKAYV8MC2j7tbvW0rhiY5pWbcr7V77Pkt+X0O+jfqSmpRZhlDnbvG8zVUpXoXSJ0iE5vzH5YQmZMcaYbCWWT+Sxro/x8aqP+WjFR7luu+fIHnYd2UVS5SQALkq6iDG9xvDZms+4e/rdIZl5mbwv2caPmbARmQmZqhWGNcaYQvDXc/7KGTXPYMi0Iew+sjvH7dbtXgdAUqWk9GW3n3U793W4jxcXvchjsx4r6lBPYEVhTTiJzIQsNdUlZZaQGWNMgcTFxPHapa/xx+E/cu26XLt7LUB6MVqfUd1HcdPpN/HEnCd4du6zRRlqJqpqCZkJK5GZkKWkuHdLyIwxpsBOr3E6D3d+mHeWvsPEZROz3Wbd7nUIQqNKjTItFxHGXTKOK5tdyV//91f+O/+/wQiZPX/u4WDKQeuyNGEjLtQBFAlfQmaFYY0xplD8vcvf+WrDV9z62a2cXftsGlRskGn92t1rqXNKHUrGlTxh39iYWMZfMZ7UtFTu/uJujqUd494O9xZpvL4ZltZCZsKFtZAZY4zJU4nYEkzoOwFB6PdRP1JSUzKtX7trbfqA/uzEx8bz/pXvc1Wzq/jr//7Kk7OfLNKB/sl7rQaZCS+WkBljjAlI/Qr1efXSV5m/bT5Dpw/NtG7d7nWZBvRnx5fUDWg9gH/M+gd3TruzyEpifLDiAxJiE3JNEo0pTiwhM8YYE7Arm13Jgx0fZOzisYxdNBbIKHmRdUB/duJi4nijzxvcf879vLjoRa7+8OpcH8+UmpbK4l8X56s1be6WuYz/ZTz3nXMfFUpWCHg/Y0LJEjJjjDH58nS3p+nVuBd3Tb+LWZtmZVvyIjcxEsOo7qMYfeFoPl75MV3e7MK2/duy3faZH56h7SttufKDK3Msu7Hvz310eK0D9864lwNHDzD0i6HUKleL4Z2Gn9wFGhMClpAZY4zJl9iYWCb0nUDjSo25bOJlTF45GSDf3YPD2g9jar+prNm1hrNeOYsftvyQaf2RY0d4dt6zNKzYkE9Xf0rrsa35euPXJxznmR+eYd7WeYyeN5rE5xJZ+OtCRl4wkrLxZU/+Io0JsoASMhHpKSKrRWSdiJzwK4eIVBSRj0VkqYgsEJEWfuuGisgyEVkuIsP8llcSkS9FZK33XrFQrggsITPGmCJWoWQFvvjLF5SJL8OI70cgCA0rNsz3cXo36c0PN/1AqRKl6PpmV/47/7/p3ZNv/PwGOw7t4PVLX2fuoLmUiivF+W+fz13T7krv5vzt4G88O+9Zrml+Dd/e+C21y9XmvPrn0b9l/0K9XmOKWp4JmYjEAi8AvYBmQD8RaZZls4eBn1W1FTAAeN7btwVwC9AOaA30FhHfr1DDgZmqmgTM9L4XjqNH3bslZMYYU2TqVajHjOtmUKFkBRLLJ2Zb8iIQLau3ZPHgxfRq3Iu7v7ibqz+8mp2HdvLvH/5Nhzod6FKvC2fWOpOfb/uZu9vdzZiFY2g1thVfbfiKp+Y8RUpqCk91e4pOiZ1YdscyvhrwFTESmR1AJnIF8je2HbBOVTeoagowEeiTZZtmuKQKVV0F1BeR6kBTYJ6qHlbV48Bs4HJvnz7AW97nt4DLCnIhmVgLmTHGBEWLai347sbvePeKdwt0nAolKzDl2imMvGAkU1ZNodF/GrFp7yaGdxqOiABQukRpnu/1PLMGziJWYun+TndeWvQSt5xxS6YJBZaMmXAUyN/a2sAWv+9bvWX+lgBXAIhIO6AeUAdYBnQRkcoiUhq4CKjr7VNdVbcDeO/Vsju5iAwWkUUismjnzp2BXZUlZMYYEzTNqzWnU2KnAh8nRmJ4oOMDfH/T91QrU40za55J7ya9T9iua/2uLLltCQ93epiW1Vry9y5/L/C5jQm1QCr1SzbLss4/HgE8LyI/A78APwHHVXWliIwEvgQO4hK34/kJUFXHAeMA2rZtG9i8586dYd06qFUrP6cyxhhTDLSr3Y5Vd67ieNrxHFu7SpUoxdPnP83T5z8d5OiMKRqBJGRbyWjVAtfy9av/Bqq6H7gRQFzb8kbvhaq+BrzmrfundzyA30WkpqpuF5GawI4CXEdmpUtDo0Z5b2eMMaZYiouJIy4mMp/uZ0x2AumyXAgkiUgDEYkHrgWm+m8gIhW8dQA3A3O8JA0Rqea9J+K6Nd/ztpsKDPQ+DwQ+KciFGGOMMcaEqzx//VDV4yJyJzADiAVeV9XlInKbt34sbvD+2yKSCqwABvkd4iMRqQwcA4ao6h5v+QhgkogMAjYDVxXWRRljjDHGhJOA2oNVdRowLcuysX6f5wLZVgRU1c45LN8FnB9wpMYYY4wxEcrmBhtjjDHGhJglZMYYY4wxISa+R1SEAxHZCSTnsVkV4I8ghFMUwjX2cI0bwjf2cI0b8h97PVWtWlTBBEuA9y8I3z/bcI0bwjf2cI0bwjf2Irt/hVVCFggRWaSqbUMdx8kI19jDNW4I39jDNW4I79iDIVx/PuEaN4Rv7OEaN4Rv7EUZt3VZGmOMMcaEmCVkxhhjjDEhFokJ2bhQB1AA4Rp7uMYN4Rt7uMYN4R17MITrzydc44bwjT1c44bwjb3I4o64MWTGGGOMMeEmElvIjDHGGGPCSkQlZCLSU0RWi8g6ERleDOKpKyLfiMhKEVkuIkO95ZVE5EsRWeu9V/Tb5yEv/tUicqHf8jNF5Bdv3X+8h7gXdfyxIvKTiHwWZnFXEJEPRWSV97PvEA6xi8g93t+TZSLynoiULK5xi8jrIrJDRJb5LSu0WEUkQUTe95bPF5H6hX0NxY3dvwo9frt/BT92u4cV5B6mqhHxwj1ncz3QEIgHlgDNQhxTTeAM73M5YA3QDBgFDPeWDwdGep+beXEnAA2864n11i0AOgACTAd6BSH+e4EJwGfe93CJ+y3gZu9zPFChuMcO1AY2AqW875OAG4pr3EAX4Axgmd+yQosVuAMY632+Fni/qP/ehPKF3b+KIn67fwUxduweVuB7WMj+sRfBD7cDMMPv+0PAQ6GOK0uMnwDdgdVATW9ZTWB1djHjHujewdtmld/yfsDLRRxrHWAm0I2MG1o4xH2Kd1OQLMuLdezezWwLUAn3jNnPgB7FOW6gfpabWaHF6tvG+xyHK8QoRXEdxeFl969Cj9XuX8GP3e5hBbyHRVKXpe8vg89Wb1mx4DVXtgHmA9VVdTuA917N2yyna6jtfc66vCg9BzwApPktC4e4GwI7gTe87opXRaRMcY9dVbcBzwCbge3APlX9X3GPO4vCjDV9H1U9DuwDKhdZ5KFn96/C9Rx2/wpq7HYPy7Q80z6B3sMiKSHLro+5WEwhFZGywEfAMFXdn9um2SzTXJYXCRHpDexQ1cWB7pLNsqDH7YnDNUO/pKptgEO4puecFIvYvbEKfXDN4bWAMiJyXW67ZLMsVD/zvJxMrMXxOopSsb1eu3+dsLwoheX9C+welmV5bvvkKJISsq1AXb/vdYBfQxRLOhEpgbuZjVfVyd7i30Wkpre+JrDDW57TNWz1PmddXlQ6ApeKyCZgItBNRN4Ng7h9sWxV1fne9w9xN7jiHvsFwEZV3amqx4DJwDlhELe/wow1fR8RiQPKA7uLLPLQs/tX4bH7V2hit3tYAe9hkZSQLQSSRKSBiMTjBtFNDWVA3myL14CVqvqs36qpwEDv80Dc2Azf8mu92RkNgCRggdd0ekBE2nvHHOC3T6FT1YdUtY6q1sf9HL9W1euKe9xe7L8BW0TkVG/R+cCKMIh9M9BeREp75zsfWBkGcfsrzFj9j3Ul7u9gqH9LLkp2/yokdv8K2X3A7mEFvYcVxUC5UL2Ai3AzgdYDjxSDeDrhmiiXAj97r4tw/cgzgbXeeyW/fR7x4l+N38wSoC2wzFs3hiANcAbOJWNQbFjEDZwOLPJ+7lOAiuEQO/A4sMo75zu4GT3FMm7gPdw4kWO43wQHFWasQEngA2AdbhZTw2D8fQ/ly+5fRXINdv8Kbux2DyvAPcwq9RtjjDHGhFgkdVkaY4wxxoQlS8iMMcYYY0LMEjJjjDHGmBCzhMwYY4wxJsQsITPGGGOMCTFLyIwxxhhjQswSMmOMMcaYELOEzBhjjDEmxP4fjzLjbI53iDAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "already_display = []\n",
    "for x in plot_list:\n",
    "    fig, ax = plt.subplots(1, 2, figsize=(10, 3))\n",
    "    if not x['public_card'] in already_display:\n",
    "        print(x['round_time'])\n",
    "        display_cards(x['exist_card'])\n",
    "        display_cards(x['public_card'])\n",
    "        already_display.append(x['public_card'])\n",
    "        print()\n",
    "        \n",
    "    ax[0].plot(x['count_list'], x['win_per'], color='red')\n",
    "    ax[1].plot(x['count_list'], x['loss_per'], color='green')\n",
    "    ax[0].set_title('Rount Time:{}'.format(x['round_time']))\n",
    "    ax[1].set_title('Count:{}'.format(x['count']))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69628c0d",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "## 多人，起始牌，蒙特卡诺模拟，5w次"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "ab2e8aee",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d7add8998d21477ba68772917a2f89db",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/6 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "aadde733afaa43c8b3e4e43fc716a9c9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/50000 [00:00<?, ?it/s]"
      ]
     },
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   ],
   "source": [
    "simulation_time = 50000\n",
    "gamer_num = 7\n",
    "plot_list = []\n",
    "\n",
    "# 获得总牌库【card_list】\n",
    "# A-♣️, B-♠️, C-♦️, D-♥️\n",
    "# 11-J, 12-Q, 13-K, 14-A\n",
    "\n",
    "card_list = []\n",
    "count_rank = []\n",
    "\n",
    "for gamer_num in notebook.tqdm(range(3,9)):\n",
    "    \n",
    "    for color in ['A', 'B', 'C', 'D']:\n",
    "        for num in range(2, 15):\n",
    "            card_list.append({'color':color, 'num':num})\n",
    "        \n",
    "    # 获得自己的手牌\n",
    "    # exist_card = list(random.sample(card_list, 2))\n",
    "    \n",
    "    # 设置手牌\n",
    "    exist_card = [transfer_card('A1'), transfer_card('C5')]\n",
    "    for x in exist_card:\n",
    "        card_list.remove(x)\n",
    "\n",
    "    count = 0\n",
    "    count_loss = 0\n",
    "    count_win = 0\n",
    "    count_tie = 0\n",
    "    win_per = []\n",
    "    loss_per = []\n",
    "    count_list = []\n",
    "\n",
    "    for i in notebook.tqdm(range(simulation_time)):\n",
    "\n",
    "        if count % 100 == 0 and count > 0:\n",
    "            win_per.append(count_win / count)\n",
    "            loss_per.append(count_loss / count)\n",
    "            count_list.append(count)\n",
    "\n",
    "        count += 1\n",
    "        othergamer_max_types = []\n",
    "        othergamer_cards = []\n",
    "        judge_tie = 0\n",
    "        judge_loss = 0\n",
    "\n",
    "        card_list_copy = card_list.copy()\n",
    "\n",
    "        # 随机模拟底牌\n",
    "        cards_todo_ = random.sample(card_list_copy, 5)\n",
    "\n",
    "        # 当前底牌下，自己能够组合的最大牌型\n",
    "        my_max_cards = get_max_type(cards_todo_, exist_card)\n",
    "\n",
    "        # 排除底牌和自己手牌后，对手可能的手牌池\n",
    "        for x in list(cards_todo_):\n",
    "            card_list_copy.remove(x)\n",
    "\n",
    "        for x in range(gamer_num - 1):\n",
    "            opponent_cards = random.sample(card_list_copy, 2)\n",
    "            for m in opponent_cards:\n",
    "                card_list_copy.remove(m)\n",
    "            # 当前底牌下，对手在某手牌中的最大牌型\n",
    "            opponent_max_cards = get_max_type(cards_todo_, opponent_cards)\n",
    "            othergamer_cards.append(opponent_max_cards)\n",
    "            othergamer_max_types.append(opponent_max_cards['rank'])\n",
    "\n",
    "        # 如果任何一家对手牌型更大，则输\n",
    "        if min(othergamer_max_types) < my_max_cards['rank']:\n",
    "            count_loss += 1\n",
    "            continue\n",
    "\n",
    "        for opponent_max_cards in othergamer_cards:\n",
    "\n",
    "            # 牌型相同，则同牌型比大小\n",
    "            if opponent_max_cards['rank'] == my_max_cards['rank']:\n",
    "                my_max_type = compare_samerank(my_max_cards['types_todo'])['out']\n",
    "                opponent_max_type = compare_samerank(opponent_max_cards['types_todo'])['out']\n",
    "                final_max_type = compare_samerank([my_max_type, opponent_max_type])['out']\n",
    "\n",
    "                # 只要出现judge_win=1，就说明至少有一家牌和自己同样大，这把就无法获胜\n",
    "                if final_max_type == my_max_type and final_max_type == opponent_max_type:\n",
    "                    judge_tie = 1\n",
    "                elif final_max_type == my_max_type:\n",
    "                    continue\n",
    "                else:\n",
    "                    count_loss += 1\n",
    "                    judge_loss = 1\n",
    "                    break\n",
    "\n",
    "            # 自己牌比对手牌大，比下一家\n",
    "            else:\n",
    "                continue\n",
    "\n",
    "        if judge_loss == 1:\n",
    "            continue\n",
    "        elif judge_tie == 0:\n",
    "            count_win += 1\n",
    "        else:\n",
    "            count_tie += 1\n",
    "            \n",
    "    plot_list.append({'count_list':count_list, 'win_per':win_per, 'loss_per':loss_per, 'exist_card':exist_card})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73ec30bc",
   "metadata": {
    "heading_collapsed": true,
    "hidden": true
   },
   "source": [
    "###  3人模拟结果，约2900it/s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "7bd27b1b",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------------\n",
      "♣️4♣️5\n",
      "-----------------\n",
      "♠️J♠️K\n",
      "-----------------\n",
      "♠️3\n",
      "♦️8\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for x in plot_list:\n",
    "    fig, ax = plt.subplots(1, 2, figsize=(10, 3))\n",
    "    display_cards(x['exist_card'])\n",
    "    ax[0].plot(x['coaunt_list'], x['win_per'], color='red')\n",
    "    ax[1].plot(x['count_list'], x['loss_per'], color='green')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ead936e",
   "metadata": {
    "heading_collapsed": true,
    "hidden": true
   },
   "source": [
    "###  4人模拟结果，约2200it/s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "0d825ca6",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------------\n",
      "♣️3\n",
      "♥️A\n",
      "-----------------\n",
      "♠️3♠️J\n",
      "-----------------\n",
      "♠️Q\n",
      "♦️4\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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5Rwrtvxq4O7S6B/iVc25BaN9LwGXAVufcCeUVeAGRidf27QX3JSWV3r5evejbjzjC381n5h9pM3lywf3TppUtThGpdM65qcDUQtvGFFp/GXi50LZVQLcKDk9EEkypY7zMLAl4Fj+4tAswxMy6FDpsNdDHOdcVeAiIvPPnZfydQhUnsquxcOIVmZQdivBDjd9809+JuHixv+Owb1+48MLDO7eIiIgklFgqXqXOg+Oc+yLi+K/wA1jD+z41s3blEm1xSqp4DRtWfu+TlubHUM2cWX7nFBERkYQRy12N0ebBaVXC8TcA7x9OUDH71a/gjDMKVrx27Mhf7tnz8B9KLSIiIlJOYql4xTwPjpmdi0+8ziprIGY2AhgB0LZt29ga7dwJ27YVX/GqWbOsYYiIiIhUmFgqXjHNg2NmXYEXgf7OuR8L7y/NIc2DY+YnPo1MvCIrXqmpZQ1DREREpMLEknjlzYNjZqn4eXCmRB5gZm2BN4Fhzrnvyj/MYoQTr8iuxoyISaeVeImIiEg1Umri5ZzLxj+7bBqwFHg9PA9OeC4c4D6gMfCcmc03s7nh9mb2GvAlcKyZbTCzG8ot+mgVr9Wr85eVeImIiEg1EtM8XqXNg+Oc+wXwi2LaDjmcAEsULfECaNzYT6Taq1eFvbWIiIhIWQV75vpoXY0AgwbBzTfnPz5HREREpBqIj8QrO7vg9lat4ISKmSRfRERE5FDFMri++iou8apVq2riERERESlBfCReOTkFt2tQvYiIiFRD8Zl4aeJUEQkQ56LOSS0icSg+Ey9VvEQkQHJdblWHICKVJD4Sr8JjvFTxEpEAUeIlkjjiI/FSV6OIBFiOyyn9IBGJC/GZeKmrUUQCRBUvkcQRn4mXKl4iEiA5uap4iSSK+Ei8Co/xUsVLRAJEFS+RxBEfiZcqXiISYEq8RBJHfCZeqniJSIBocL1I4ojPxEsVLxEJEFW8RBJH/CReZvnbVfESkQDR4HqRxBH8xAv84PqkpPztqniJSICo4iWSOIKdeEF+xSspCWqEPo4qXiISYmZ9zWy5ma0ws3ui7L/TzOaHXovMLMfMGkXsTzKzb8zs3YqKUYmXSOIIduIV2dUYmXip4iUi+KQJeBa4GOgCDDGzLpHHOOf+7Jzr7pzrDtwLfOKcy4g45FZgaUXGqcH1IokjfhKv5GRVvESksFOBFc65Vc65g8AEoH8Jxw8BXguvmFlr4FLgxYoMUhUvkcQRH4lXeIzXJZf47Uq8RMRrBayPWN8Q2laEmaUBfYE3Ijb/BbgLqNDMKDs3u/SDRCQuxEfiFe5q/Ne/4LvvlHiJSJhF2eaKObYfMCvczWhmlwFbnXPzSn0TsxFmNtfM5qanp5c5yN0Hdpe5jYgEU3wlXrVrQ8eOVR2ViFQfG4A2EeutgU3FHDuYiG5GoBdwuZmtwXdRnmdm46M1dM6Ndc71dM71bNq0aZmD3HVgV5nbiEgwxU/ilZxc1dGISPUzB+hoZu3NLBWfXE0pfJCZNQD6AG+Htznn7nXOtXbOtQu1+9g5N7QiglTiJZI44iPxKjyPl4gI4JzLBkYB0/B3Jr7unFtsZiPNbGTEoQOB6c65zKqIc+eBnRV6/n1Z+9iauRUA54rraRWRyhAfiVe4q1FEpBDn3FTnXCfnXAfn3B9D28Y458ZEHPOyc25wCeeY6Zy7rKJirOiK17HPHEubJ9vw3Y/fUe9P9Rg9Y3S1TsDe//59ujzbhUGTBvHPBf/kYM5B3v3uXdbvXF96Y5FqLtj9c0q8RCQOVGTitXr7atbv8gnLI58/QmZWJg9++iDpe9N55pJnqGHV5+/vb7d8y6j3R/H5us/Jdbks3baUfy/5N8PfGg5A8zrNWTZqGQ1rNYzafm/WXtJS0ioxYpGyqz7/4w6FEi8RiQM791dcV+MHKz7IW/77/L/nLT8/93neWPJGtCbFyjyYyeuLX8c5x96svfz2o9+yZscaZq2bddgVtIM5B7lo/EV8uvZTcl0u7/38PR45/xGu6XYNvdr04qy2Z7Elc0uxMd/03k20eqIVry58lR37dxxWLCIVKaaKl5n1BZ4CkoAXnXOPFNp/NXB3aHUP8Cvn3IJY2h6WyDFeGlwvIgESmahU5BivCYsn0KVpF5akL/HrP53A4Dd8r+qHqz5k0PGDYj7X7dNv54V5LzDnjDk8P/d5MrMy+dPnfwLg0Qse5Zpu19Cibosi7b5c/yUDJw7k/y78P67uenXe9v3Z+7lq0lU0rNWQVxa+krf9xGYn0veYvlzS8ZK8bc45jn/ueB6d9SjDuw/n7g/v5q3lb3F99+uZtnIan637DIChk/39Dye3PJkL2l/Apj2bWJq+lEmDJtH+iPYxf1aRilJqxSuWR24Aq4E+zrmuwEPA2DK0PXSqeIlIQLmI6cT2Zu2tkPfYl7WPL9d/yWUdL+Pl/i9zeuvTGdh5IJN/NhmAv339N1ZtX1XqeTL2ZXDN5Gt4Yd4LADz+5eNkZmVSMyn/8Wx3/+duOj/bmQ27NpDrcpn/w3ySHkzigZkPcOZLZ7IlcwsTFk/IO/6fC/7JSS+cxDvfvZOXdJ3X/jy23LGFOTfOKdIFamaM7jOa7zO+J+WhFJ746glWbV/F72f8ns/WfcaA4waw5KYlPHzuwwB8vflrHvviMcYvHM+8zfP442d/PLxvpkg5iaWrsdRHbjjnvnDObQ+tfoWfKyemtodFiZeIxIHMrIq5mfKj1R+RlZvF2UedzfDuw/nyhi9JTUplwHEDOLXVqQBs2LWhSLuJiyYya92svPUb37mxQEUKYPYvZvPi5QWfpLRj/w7aPNmGPi/34enZT5Prcrn/k/tJTfKTWr/73bv8Z9V/yM7NZvhbw1m2bRldmvq/xcdcOoaPrvmIZnWaUTM5+vN2L+10ad7ybafdxnFNjgOgXcN2vHT5S3Ru2pnf9f4d+3+3nwk/9UneN7/8hsEnDGbcN+M45+Vz2Je1r8A5V2Ss4P3v3y/yXjv376zWNyBIcMXSPxftkRunlXD8DUD4pzjmtmY2AhgB0LZt2xjCQomXiARW5C/1iqh45eTm8NuPfkv7hu254OgLiux//tLn6TG2Bxn7MorsC3dFutE+xi/XfwnAlMFTyHW5nNv+XOrXrE+nxp0Y1GUQH6z4gN0H82ff/3zd53y+7vO89a13bGVv1l5O+dspXPn6lTx50ZMA3Nf7Ph449wH2Ze2jdkrtUj9T3dS6LLlpCW0atKFual2e5EnW7ljLUQ2PKnBczeSa/OyEn3FJx0uoV7Me9/W+j3eWv8Mnaz/hjul38Oylz5KTm8Pf5/+dG9+5EfCJX0pSCvfPvJ8aVoO1O9dyZpsz+Wvfv5JcI5k7P7yTZnWa8VL/l/ISSZFDEUviFfMjN8zsXHzidVZZ2zrnxhLqouzZs2dsf2ZoAlURCaiK7mr8bN1nfLv1W1694lVqJdcqsr9x7cYA/Lj3xwLbI++wnLhoIqe1Po0tmVv4Q+8/0O/YfgWObVirIa8Pep0te7Ywdt5Y7pt5H4NPGMy8TfNYs2MNn1z7Ccc0OoYGtRrQoFYDfn3ar7n7P3dz/ZTrAfjVKb8CiCnpCuvctHOB9cJJV6R6Nevltdnz2z1c9/Z1vLLwFS465iJGvDOCLZlb8o4d+d7IIu2/WP8FPf/Ws8C2Lk27cO9Z92IW7debSOli6WqM6ZEbZtYVeBHo75z7sSxtD5kmUBWRgIqseGUezGT9zvXYA8b0ldMP6Xyrtq/iV+/+Kq8r7asNXwHQ95i+UY9vVLsRQJGK18qMlXnLg98YTPun2pPrcuneonux7928bnP+0OcP7LpnF+MHjmfRTYvYdtc2zmhzBk3r5D9C6dKO+V2F/Tr1izoQvyJd1OEidh/cTf8J/UlLSePa7tfS/9j+bL97O49d8BhH1DqCb375Dbn35eZV+wBqJddi1vWz6HNUH3738e+4fsr1ZOdmc9Wkqzj5hZNZvHUxL8x9gYc/fbhSP48EUyxlorxHbgAb8Y/O+HnkAWbWFngTGOac+64sbQ9L+C8OdTWKSMAUrniFp3p4e9nbXNjhwjKf75n/PsOYeWM4ptEx3H7m7czeOJtjGh2Tl2AVVje1Lik1UvhxX37F60D2gbyutzb12+TN//XzE3/OgOMGlBpDuMKURFLU7rjjmx3Plju2UCelDsk1Kr+XIrLLdXSf0QzvPjxv/c5ed3LHmXcUqGQtGLmAzbs3c2GHCzEzxl0+joETB/Ly/Jdp37A9k5ZMAuCE50/Ia3PKkafQrmE7/vLVXxgzbwwNajZg3oh5dGjUoRI+oQRBqT/5zrlsMws/ciMJeCn8yI3Q/jHAfUBj4LnQD2126IGxUduWW/SRiVdKSrmdVkSkMu3N2svSbUsB6NS40yGdo25qXQD+vfTfnNTyJGZvmM157c8r9ngzo1HtRqRnpudtm7h4IvM2zwNgyc1LmLNxDtm52ZzX/rxym2i1WZ1m5XKeQ9EkrQm3n3E7S7ct5addflpkf+Huw67Nu9K1ede89Q6NOvDhsA/p+HRHRs8cTc2kmgw+YTAfrf6Ih899mN/P+D19Xy1YYdx5YCen/O0UvvnlNxzV8Cicc9Wmm3L3gd18n/E9R9Y7kox9GXk3OoQ550jfm87KjJW0bdCWVvVbVVGk8SWmPzmcc1OBqYW2RT5u4xfAL2JtW27CP7xZWVA79jECIiJVrfDg+nBicyDnwCGdL5xAfbXhK87/5/kAnNaqpPugoFuLbnyx4QvAj/WavWF23r66qXU5t/25hxRLdfb4hY8fVvvmdZvz4bAPGTBxAA+e8yA39rgxb98Vna9g3Dfj2LhrI7ecdgtZOVl8svYTbphyA+2easfVJ17N5GWTGXf5OAafUOwTqvI453h/xfs0SWvC/B/mc1yT4+h9VO/Dih/8OL7LX7ucT9d+WqDyOuqUUTRJa8L3Gd/z6rev0qxOs7xnfDau3Zj7+tzHqFNHRU3Cs3OzeW7Oc4xfOJ5dB3bx8HkPc2S9I3n3u3e55dRbaFmvZd6xe7P2kpWTRYNaDcjKySIlKb9wsm7nOlrWbVlgW7wJ9oj0cOKlMV4iEjCRv/AyszLzut4OZB9a4rV179Yi26JVdSJd2vFSbv3gVh785EFGzxydt33Vr0uf2yuRndb6NDb9z6Yilat6Netx2+m3FdjWrmE7Plz1IRMWTeDVb18luUYyN75zI2e2OZO2Dfwd/AdzDhbpml21fRVnjjuzwA0AAG8PfpvOTTozZfkU6qbW5fqTri81ScnJzWHdznXMXDOT5+c+z6Kti9iXvY/fnvVbOjftzLdbvuWrjV/xzJxnCrTbmrmV2sm1aVW/FSsyVnDrB7cyZfkU/jHgHxxZ70hmrZ/FrgO7ePHrF3lr2Vs4XN4UH4MmDaJWci32Z+/nuTnPcdvpt1EvtR4z187k49Ufk52bTafGnVi8dTE9juxBalIqi7YuYteBXaSlpHFyy5P5ydE/4a5ed0W9OSTI4iPxyspS4iUigRKueKUmpbI3a2/e+qFWvLZmbs2bob5OSh2mXj2VI+sdWWKbIScM4fbptxdIuq7ofIVmeI9BrN2FSTWSeO2nr3HHGXewcfdGujbvyvHPHc/Fr17M+e3PZ/mPy5mxegbPXvIs3Vt0Z9T7o2ia1pTF6YvZkrmFpmlNubLLlbSq14qn//s0/ScUnArz7/P/TnKNZI6ofQRPXvQkdVLqUDe1Lgu2LGDuprkM6zqMQZMGMWPNjALt3rjqDa7ofEXe+s79O3n8i8fJdbmM6DGC5T8up/dRvfOSnpzcHJ6f+zz3/OceOj3TiYM5B8nOzS5wzscueIw7e93Jpt2buGHKDaTUSOGabtfw4CcP8sAnD+Qdd2zjYzm99ems27mOK7tcydebv2bl9pUMPG4gm/dspnX91qzevprRM0fz+uLX+WDoB7Su35pDlZ6Zzq4Du1iSvoTVO1ZTO7k2reu35uKOFwN+/rmtmVtp37A9O/bvYPrK6TSs1bDAvHHlKT4Sr+xsjfESkUAJV7zqpNThYM5B9hzcAxx6xSs9M51uLboxus9oTm11Ku0atiu1TdM6TWnXsB0rMlZwZL0j+fTaT0ucnkEOXY8je9CDHgBM/tlkbnrvJp7+79N5+0e8O6JIm5nDZ3JGmzPyqmEDjhvAuG/GsS9rH+e0O4eHPn2I2Rtnk5qUysGcg7z73btFzvGbab8BoFebXvyyxy9JS0mjQ6MORe5SbVCrAQ+d91DeeuGfg6QaSYw6dRQ9j+zJn7/4M28ufZMLO1zIyS1OZtDxg2hcu3FemyPrHcn7V+dPSntllyvZtncbq7avYkn6EoZ1HUZSjfxiSa7LZcueLQW6IwFfKfvgNvpP6M9n131GWkoa83+Yzxfrv+Dstmfz1Oyn6NS4E9efdD1rd6ylWZ1mrN6xmrqpdWlcuzEfrPiArzZ+xfiF44skieHvZ4s6LRj79VhyXS5HH3E0O/bvyBvv1veYvgXiLC/BTrzCsrI0j5eIBFLtlNps3789b/6sw6l4NUtrxlXHX1Wmdm3qt2FFxgrObnu27ryrJBd2uJDvb/mehVsWcmyTYzGMBz95kDmb5nDzKTcz/4f5nNzyZPq061Og3fHNjueJi57IW7/q+Kv8v3udZoxfOJ7Hv3yclBopdGveje4tujNr/SxSk1IZ1nUYP+nwk3KJ/fTWp/PGVW+wbe82mqQ1ibldk7QmNElrkvfEhEg1rEaRpAvgplNuok39Nlw+4XLq/G8deh/Vm9kbZhf5P3L3f+4u0jYsLSWNs9qexXGNj+PSTpfSun5rNuzawO8//j1vLXsL8I+qGnDsAEbPHM2uA7u44aQb+N/z/7dCki4IeuIV2dWoxEtEAiTctRge23Uw5yBQ9orXrgO7yDyYyfb92w/pjsHwL7zD6cqRsjMzurXolrf+x/PznyXZ/7jYnqxnZjSv2xyAYd2GMazbsAL7bzntlnKINLqyJF2Ho9+x/XjzqjeZvGwyExdP5OJjLuba7tey4IcFdGzckdrJtVmSvoSjGh7Fp2s/5aIOF/H6ktepm+LHv53S6pQi4+e6t+jOZZ0uI2NfBsk1kqmXWg8z47qTrmPPwT0VPr9csLOVcOJ18KASLxEJlHBXY96g+tBf8ftz9pfpPOf+41y+3vw1cGhTNSSZ/6u+V5teZW4rUhkGdh7IwM4DGdtvbN6Ys8h55QZ2HgjA0K5DgdJvKgkrPMdd3dS6edOyVKRgZyuRFS+N8RKRAClc8QpXuspS8XLO5SVdcGiJ1wPnPMCZbc6MaYJUkaoUL3c3xk/ipYqXiARQuOIUrniVZYzX5j2bC6xHPp4nVu2PaM/InkWfUygiFaN8piKuKkq8RCSgCnc1HsoYr+XblhdYP6qB7kgUqe6UeImIVIFiuxrLUPFakbGiwLoe6SJS/cVH4nXwoMZ4iUigFDe4viwVrxUZK0ipkX/tK6/nKYpIxQl2mShy5mBVvEQkQEqqeL2x5A3q16xf4txLWTlZvLLwFU5rfRr39LqnwuYcEpHyFexsRYmXiARcOGGKrHhdOelKANxoV2y7Tbs3sXnPZh4696EKe7SJiJS/YNellXiJSCnMrK+ZLTezFWZ2T5T9d5rZ/NBrkZnlmFkjM6tlZv81swVmttjMHoh2/kMV7moM39UYHly/++DumNr/uO9HoPImshSR8qHES0TilpklAc8CFwNdgCFm1iXyGOfcn51z3Z1z3YF7gU+ccxnAAeA851w3oDvQ18xOL6/YCnc1hq3dsTam9hn7MoCik0CKSPUWP4mXBteLSFGnAiucc6uccweBCUBJz2MZArwG4Lw9oe0poVfxfX9lVHhwPfjB8S7Gt/hxr694NU5rXF4hiUgliJ/ESxUvESmqFbA+Yn1DaFsRZpYG9AXeiNiWZGbzga3Ah8652cW0HWFmc81sbnp6ekyBRat4dWverbjDi/hqw1eAKl4iQaPES0TimUXZVlxJqR8wK9TN6A90LifUBdkaONXMTojW0Dk31jnX0znXs2nTss0eH3k3YuemnWNqk5WTxV9m/wVQ4iUSNEq8RCSebQDaRKy3BjYVc+xgQt2MhTnndgAz8RWxchGtq7FWUi1a1StYkNubtZeNuzYW2Ja+N7+qlpqUWl4hiUglUOIlIvFsDtDRzNqbWSo+uZpS+CAzawD0Ad6O2NbUzBqGlmsDFwDLyiuwaF2NyTWSi8w+f+ErF9L6ydZMXzmd+2bcx76sfWzZswWAf13xr/IKR0QqSbCzFQ2uF5ESOOeyzWwUMA1IAl5yzi02s5Gh/WNChw4EpjvnMiOatwT+EbozsgbwunPu3XKLLUrFK7lGMg1rNcxbz8nNYdb6WQBcNP4iAE5tdWpem6Ma6tmMIkETP4mXKl4iEoVzbiowtdC2MYXWXwZeLrRtIXBSBcYFlJx4Ld22tEi7zbs353UvNq/TvKLCE5EKoq5GEZEqFJ5AFUKJV82GeesnPn9igX0Az8x5hi2ZvquxeV0lXiJBo8RLRKQKFNfV2Kttr6jHN6jZAICFWxZy93/uJrlGMnVT61Z8oCJSruIn8dIYLxEJkHBXY+GK17Cuwxh43MAix6elpBVYz87NrtgARaRCxE/ipYqXiARItIpXUo0kzIxXr3iV+jXrFzi+dkptPr/u80qNUUTKX0yJVwwPmT3OzL40swNmdkehfbeGHjy72MxuK6e4wyfPX1biJSIBUtzgevBJ1m2n3Vbg+Ms7XV5sN6SIBEepiVcsD5kFMoBfA48XansCcCP+eWndgMvMrGM5xF2UEi8RCaDImesjk7AWdVvkLY8fOJ5HLngEgP2/2+/bRXRRikhwxFLxKvUhs865rc65OUBWobadga+cc3udc9nAJ/j5csqHKl4iElBRuxojkqlOjTvlLfdq2ysvQauZXJOJV05k4a8WVlKkIlKeYkm8Yn7IbBSLgN5m1jj0ANpLKPj4jjyH8pDZAolXkyYxhiQiUvWidTXWTK6Ztxz53MbC83VddfxVdGlauONBRIIgljJRWR4yW/Ag55aa2aPAh8AeYAEQ9VYc59xYYCxAz549Yzp/gcSra9eYmoiIVAfRKl41k/ITr5Z1W9I0rSlntDmD2im1Kz0+EakYsSReZXnIbBHOuXHAOAAz+9/Q+cpHOPFq3brcTikiUhmiVbxqJdfKWzYz1v1mXYFkTESCL5auxpgeMlscM2sW+toWuAJ47VACLebkBb+KiARM5LiuyK5G8ImY6fomEldKrXjF8pBZM2sBzAXqA7mhaSO6OOd2AW+YWWP8wPubnXPbyy368AWpRrCnIxORxBOtqzGy4iUi8SmmWwFLe8isc+4HfBdktLZnH06AJVLFS0QCKm/m+ojpJNStKBL/gl0qUuIlIgEVdXB9shIvkXinxEtEpAqUNrheROJTfCReGuMlIgFVYHC9uhpF4l6wMxZVvEQkoDS4XiQxKfESEakCpc1cLyLxSYmXiEgVUMVLJDHFR+KlMV4iEjCaTkIkMQU7Y1HFS0QCziIeh6uuRpH4p8RLRKQKhLsaI6mrUST+KfESEakC4a7GyGcxpialVlU4IlJJYnpkULWlMV4iElDhipdhbPjNBuZsmkMN07VMJN4F+3+5Kl4iUgoz62tmy81shZndE2X/nWY2P/RaZGY5ZtbIzNqY2QwzW2pmi83s1vKMK7Li1ap+KwYcN6A8Ty8i1ZQSLxGJW2aWBDwLXAx0AYaYWZfIY5xzf3bOdXfOdQfuBT5xzmUA2cDtzrnOwOnAzYXblkuM6PolkkiUeIlIPDsVWOGcW+WcOwhMAPqXcPwQ4DUA59xm59zXoeXdwFKgVXkFFm1wvYjEv/hIvDTGS0SiawWsj1jfQDHJk5mlAX2BN6LsawecBMwupu0IM5trZnPT09NjCiza4HoRiX/xkbEo8RKR6KJlNcWVmvoBs0LdjPknMKuLT8Zuc87titbQOTfWOdfTOdezadOmMQUWObheRBJHsDMWdTWKSMk2AG0i1lsDm4o5djChbsYwM0vBJ12vOufeLM/AVPESSUxKvEQkns0BOppZezNLxSdXUwofZGYNgD7A2xHbDBgHLHXOPVFRAariJZJY4iPxUlejiEThnMsGRgHT8IPjX3fOLTazkWY2MuLQgcB051xmxLZewDDgvIjpJi4pt9g0uF4kIcXHBKqqeIlIMZxzU4GphbaNKbT+MvByoW2fE32MWHnFBairUSTRBLtUpMRLRAJKg+tFEpMSLxGRKqCKl0hiio/ES2O8RCSgVPESSSzBzlhU8RKRgNLgepHEpMRLRKQKqKtRJDEp8RIRqQIaXC+SmGJKvMysr5ktN7MVZnZPlP3HmdmXZnbAzO4otO83ZrbYzBaZ2WtmVqu8gs+jMV4iEjCqeIkkplIzFjNLAp4FLga6AEPMrEuhwzKAXwOPF2rbKrS9p3PuBCAJP3N0+QhduFTxEpGgUsVLJLHEUio6FVjhnFvlnDsITAD6Rx7gnNvqnJsDZEVpnwzUNrNkII3in5NWdkq8RCSgNLheJDHFkni1AtZHrG8IbSuVc24jvgq2DtgM7HTOTS9rkCW8gf+qxEtEAkZdjSKJKZbEK9pVIaY/1czsCHx1rD1wJFDHzIYWc+wIM5trZnPT09NjOX1+4qUxXiISMBpcL5KYYslYNgBtItZbE3t34QXAaudcunMuC3gTODPagc65sc65ns65nk2bNo3t7Lm5/qv+YhSRgFHFSyQxxZJ4zQE6mll7M0vFD46fEuP51wGnm1ma+avL+cDSQws1CnU1ikjAqeIlkliSSzvAOZdtZqOAafi7El9yzi02s5Gh/WPMrAUwF6gP5JrZbUAX59xsM/s38DWQDXwDjC236JV4iUhAaXC9SGIqNfECcM5NBaYW2jYmYvkHfBdktLajgdGHEWNJgfmvGuMlIgGjrkaRxBTsjEVjvEQkoDS4XiQxBTvxUlejiASUKl4iiUmJl4hIFVLFSySxBDvxCnc1aoyXiASMBteLJKZgZyxKvEQkoNTVKJKYgp2xqKtRRAJKg+tFEpMSLxGRKqCKl0hiio/ES12NIhJQqniJJJZgZyyax0tEAkqD60USU7ATL3U1ikgpzKyvmS03sxVmdk+U/Xea2fzQa5GZ5ZhZo9C+l8xsq5ktKu+41NUokpiUeIlI3DKzJOBZ4GKgCzDEzLpEHuOc+7NzrrtzrjtwL/CJcy4jtPtloG9FxKbB9SKJKT4SL43xEpHoTgVWOOdWOecOAhOA/iUcPwR4LbzinPsUyCj+8EOnipdIYgp2xnLyyf5rv35VG4eIVFetgPUR6xtC24owszR8deuNsr6JmY0ws7lmNjc9Pb1sbVXxEkkoyVUdwGE54QTYtw9q1arqSESkeoqW1RQ3qr0fMCuimzFmzrmxwFiAnj17xjRqvk+7Pqy4ZQWt6kfNA0UkTgU78QIlXSJSkg1Am4j11sCmYo4dTEQ3Y0VLS0mjQ6MOlfV2IlJNBLurUUSkZHOAjmbW3sxS8cnVlMIHmVkDoA/wdiXHJyIJRomXiMQt51w2MAqYBiwFXnfOLTazkWY2MuLQgcB051xmZHszew34EjjWzDaY2Q2VFbuIxKfgdzWKiJTAOTcVmFpo25hC6y/jp44o3HZIRcYmIolHFS8RERGRSqLES0RERKSSWHgSv+rEzNKBtTEe3gTYVoHhVBTFXfmCGnsixH2Uc65pRQZTWXT9qvaCGrvirnwVcg2rlolXWZjZXOdcz6qOo6wUd+ULauyKO34F9XsU1LghuLEr7spXUbGrq1FERESkkijxEhEREakk8ZB4ja3qAA6R4q58QY1dccevoH6Pgho3BDd2xV35KiT2wI/xEhEREQmKeKh4iYiIiARCYBMvM+trZsvNbIWZ3VNFMbxkZlvNbFHEtkZm9qGZfR/6ekTEvntD8S43s4sitvcws29D+/5qZhbaXtPMJoa2zzazduUUdxszm2FmS81ssZndGoTYzayWmf3XzBaE4n4gCHFHvGeSmX1jZu8GLO41ofecb2ZzgxR7daXr12HFHcjrV+i8uoZV/ve8+l2/nHOBewFJwErgaCAVWAB0qYI4egMnA4sitj0G3BNavgd4NLTcJRRnTaB9KP6k0L7/AmcABrwPXBzafhMwJrQ8GJhYTnG3BE4OLdcDvgvFV61jD71H3dByCjAbOL26xx0R//8A/wLeDcrPSuh8a4AmhbYFIvbq+ELXr8ONO5DXr9C5dA2r/O/5GqrZ9atS/6OX4z/+GcC0iPV7gXurKJZ2FLxwLQdahpZbAsujxYh/aO8ZoWOWRWwfArwQeUxoORk/kZtVwGd4G/hJkGIH0oCvgdOCEDfQGvgIOI/8i1a1jzt0vjUUvXAFIvbq+ELXr/L+DIG7foXOq2tY5cS9hmp2/QpqV2MrYH3E+obQtuqguXNuM0Doa7PQ9uJibhVaLry9QBvnXDawE2hcnsGGyqIn4f/yqvaxh0rd84GtwIfOuUDEDfwFuAvIjdgWhLgBHDDdzOaZ2YiAxV4d6fpVToJ2/QrFrGtY5cZd7a5fyYf8UaqWRdnmKj2Ksiku5pI+S4V+TjOrC7wB3Oac2xXqso56aDFxVHrszrkcoLuZNQQmm9kJJRxeLeI2s8uArc65eWZ2TixNiomhqn5WejnnNplZM+BDM1tWwrHVLfbqKIift9r9uwbx+gW6hhWzvaQ2h6vaXb+CWvHaALSJWG8NbKqiWArbYmYtAUJft4a2FxfzhtBy4e0F2phZMtAAyCiPIM0sBX/RetU592aQYgdwzu0AZgJ9AxB3L+ByM1sDTADOM7PxAYgbAOfcptDXrcBk4NSgxF5N6fp1mIJ+/QJdwyop7mp5/Qpq4jUH6Ghm7c0sFT+gbUoVxxQ2BRgeWh6OH38Q3j44dAdEe6Aj8N9QmXO3mZ0eukvimkJtwue6EvjYhTqSD0fofcYBS51zTwQldjNrGvorETOrDVwALKvucTvn7nXOtXbOtcP/rH7snBta3eMGMLM6ZlYvvAxcCCwKQuzVmK5fhyGo169Q7LqGVe7vjOp5/TrcgWtV9QIuwd/NshL4XRXF8BqwGcjCZ7034Pt2PwK+D31tFHH870LxLid0R0Roe8/QD8NK4BnIm9i2FjAJWIG/o+Locor7LHwpdCEwP/S6pLrHDnQFvgnFvQi4L7S9Wsdd6DOcQ/7A1GofN/7OuwWh1+Lw/7UgxF6dX+j6dThxB/L6FTqvrmGV+zujWl6/NHO9iIiISCUJalejiIiISOAo8RIRERGpJEq8RERERCqJEi8RERGRSqLES0RERKSSKPESERERqSRKvEREREQqiRIvERERkUry/7uSkWidjA6wAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for x in plot_list:\n",
    "    fig, ax = plt.subplots(1, 2, figsize=(10, 3))\n",
    "    display_cards(x['exist_card'])\n",
    "    ax[0].plot(x['count_list'], x['win_per'], color='red')\n",
    "    ax[1].plot(x['count_list'], x['loss_per'], color='green')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6612967a",
   "metadata": {
    "heading_collapsed": true,
    "hidden": true
   },
   "source": [
    "### 8人模拟结果，约1150it/s (5人约1800it/s，6人约1500it/s，7人约1280it/s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "d3b09050",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------------\n",
      "♣️Q\n",
      "♠️2\n",
      "-----------------\n",
      "♣️6\n",
      "♦️6\n",
      "-----------------\n",
      "♠️Q\n",
      "♥️Q\n"
     ]
    },
    {
     "data": {
      "image/png": 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mv8Lo+aP9aUkJSblO6JpWMY1/nvNPEhMSufq07KkvK6RUYM9DeyibXJZb297KoYxDACQmJHJG3TP8k37e2+HeHIGeT6MqjRjea7h//1/n/YvfNv3G2EVjefb8Z3M9zwQ7lHGIhVsX8sHcDxj++3Ba1GzBR//3EZ8u/JRp66bx9LlPsz99v7+ZO5xqZapx4UkX8uovr/L9yu+ZsWFG2HypSanc3PpmHu3yKPUr1S+kT1TyxeZfZrigzKbEMMZEmWNpvnxqylP8tPYnyiaXpU75Orze83Ue6fwI5VPKU6tcLf8al77+X4POG5Rnn7FzGoSvjQp1eu3TOZJ1hCemPOFPC7eGpo+I8Pcufw97rHyKay5te0LboPQHOj3AxOUTAbi/4/0RlcvnjnZ30Gt0L8YsGBMUBMaT9Mx05m6em+PnGmjG+hkcyTrC+j3ruW/iff5RtWfXP5vfNv5GvZezF+mZt3le2AlV61Wox6DzBvHU/57itq9u43DmYX86uL+VWRtn8UCnB2hVqxV/bP+DK0+90j+CMp7FZlBmzZfGmBhwLM2X/5jsFgnvULcDtcvXJjkx2V/zkFYxjR9W/YCqsmnfJkonlaZyas7RaxVSKrDn8B4mXT/J33H+aFrVagXAjoM7uK7Fdbw/9/2w1z4e3U7sxsG/H2TnwZ357vR90ckX0aRqE9767a0cQdmirYvo/1V/njrnKbo26FqAJS5ZXp72Mg9NeogbW93Ic+c/R9UyVYOOv/P7O9w47kb/fumk0rza/VVOr306Z6adyfR103li8hP0bd6XgxkH+cvXf6FsqbIM+dMQrj7tauZvmU+55HK0qNkCcE3hI+eMZPuB7Vx16lXc0OqGIv280Sg2gzIbfWmMiQHH03y5ZNsSup0YPD93g0oN2HN4D7d/fTuzNs7yTxobasqfpzBuybg8J4wNdXLVk7m+5fW8N+c9zq5/Nne2vzNoOaeCkpqUekyj8BIkgR6NejB01lAOZxxm1LxR/Lr+V5ITk9lxcAdT10zlnJHnhF1RoKRIz0zn57U/Uzm1Mi1rtcz3+ROWu9UdRswewegFo5lxywyaVmvKJws/Ycv+Ldz9rZuypGrpqrx4wYtc1vQyf60luED/22u/9e93bdCVGmVr+GtaO9XrFHS/8048j/NOPC/f5YxnsR2UWU2ZMSaK5bf5cuqaqf7tnYd2UjGlYtDxmmXdyMqhs9yCLO1OaBf2Oq1qtfLXfEVKRBh56UjuOeMeTqt5Wonst3X+Sefzyi+vcMnoS/zNoD5n1z+bKaun8MLPL/DplZ8WUwnDO3jkID+t/YlrPruGLfu3UKNsDTbct4HEhMQcebcd2EbppNKUTS7rT1NV/rviv/xv9f94oNMDlC5VmienPEnbYW1pUbOFv3+hIPwx4A//oIujCVzyyhSMkvevpiBY86UxxiMi3YFXcevvvq2qg0KOVwQ+ANJwz8QXVPUd79i9wM2AAvOAfqp6SESqAB8DDYBVwJWqupMClt/myw/nfRi0HxqUdanfJWh/7Z7IFhHPj9a1Wxf4NQtKj0Y96Fi3oz8gu/CkC6lRtganVj+V+zvdz9Vjr/av9VlUVu1axdb9W3l/7vvULFuTRzo/QpZmMW3dNACGzBwS9Hu98KQLmbB8AhOXT6RZ9WZMWjmJG1u7JsehM4fyt+/+xr70fZxQ/gQe6PQAny/5nMmrJvvPH9B+APUq1qP/6f25adxNrNq1ijd7vkmTak1ISkiKOCAzhSM2gzJfTdmEgIV4LSgzJu6ISCLwBnA+sA6YISLjVDVwZtU7gIWqerGIVAeWiMgooDpwF9BMVQ+KyBigD/Au8BAwSVUHichD3v6DBV3+/DZf7j+yn/oV69O8RnO+Xvo1FVODg7J6Feuhj7v+ZLVfrE3DSg0Lsrglnogw/JLhNHuzmVuwus/npCal+o93rNuRTxZ+QvcPunNZ08s4s96ZnFrj1KBrqGquI0pnb5rNtLXTuKnNTSQnJudZlq37tzJ05lB/H0Cfcxqew/DfhjNi9ogc57xy4Sv8pd1fqPNSHZ7/+Xl+WPUDAA0rNeSntT/x2A+PAW6Kkw17N3DPhHuCzn/krEeoV7GeP88313yTZxlN0YvtoGzBguw0C8qMiUftgWWqugJAREYDvYDAoEyB8uL+py0H7AAyvGNJQGkROQKUATZ46b2Art72SGAyhRCU5bf5cu/hvZRLLucf5Ra4fFKgWuVqMfvW2dQqV+u4yxhtmlZvij6uZGlW0ILrALe2vZVf1v/C5FWT/f2vAiecnbRiEld+eiUnVj6RVy58hTPTzgw6/4bPb2Du5rlkZGVw5xl35lqGwxmHuWzMZUxdM5XTapzGNaddQ8/GPekwvAOPTHokaPJUXxla1WrlL++TXZ/kjvF3+I+f+57r+9e3eV/e6fUOKUkpHDhygC+XfEnjqo1ZvG0xlzS5hHLJ5Y7xp2aKSmwGZeG+xdiUGMbEozpAYBvdOuCMkDyDgXG4gKs8cJWqZgHrReQFYA1wEJioqr6OSDVVdSOAqm4UkbwXhzxG+W2+3Je+j/Ip5SldqjSQPVFnOMfSUTyWhAZk4OZoG335aHYf2s2tX93Kxws+5vRhp9Omdhu27N/inx5ix8EdnPXOWfx84890rNcRgO0HtjNv8zwAXpj2Alc1v4oL3r+AVbtW0aZ2G8oml2X1rtXUq1iPrfu3MmPDDB4880Ge6faMvyx/7/x3/v69myZk3l/msfvQbsoll8vxu7q93e1USKnA4F8Hs/PQTs5reB6XN7ucrg26+mvxypQqw1XNrwKwVQyiSGwGZQlhFiqwmjJj4lG4dqbQSOdCYDZwLnAS8J2I/Ijrg9YLaAjsAj4RkWtV9YOIby7SH+gPkJaWFnGhO9btyLR10/LdfLk33dWUlU5yQVle84SZ3FVMrcjoy0fz3PnP0f2D7mzYu4EqpatwRbMrePNPb9LurXas2rWKTiM6sWTAEk6uejLDfx+OojzZ9Uken/w4NV+oSaIkUqtcLX8zI8C8LS5we7fXu1zf8vqgptD7O97Pip0rqJBSgeY1mudZxmtbXMu1La7NM4+JPhaUGWNi2TqgXsB+XbKbIH36AYPUVUstE5GVwClAfWClqm4FEJHPgE64QQGbRaS2V0tWG9hCGKo6DBgG0LZt24gjrMe6PEbPD3vmu/lyX/o+aperTfdG3Xlm6jOcXf/sfJ1vgqVVTGPObXNyrEww5c9TOHPEmazbs44JyyawcOtCHvrvQ5xR5wwe6/IYE5ZP4Oe1P/PWxW5OtLmb51KvYj1mrJ/BuCXjuKTJJVzc5OIc90tJSuHtS94uyo9oSpjYDMrCNV9aUGZMPJoBNBaRhsB6XEf90Onc1wDdgB9FpCbQBFiBq2XrICJlcM2X3QDf0LxxwA3AIO/9i4IstC8AyG/zpa9PWef6nTnwyAF/M6Y5duGWmEqrmMbae9fSZHATXpz2IrsO7aJ17db89/r/IiL8cMMPrN29lpOqnARAuzpu6pGLm1wcNhgzxic2FyS3mjJjDKCqGcAAYAKwCBijqgtE5DYRuc3L9hTQSUTmAZOAB1V1m6r+AnwK/IabDiMBr9YLF4ydLyJLcSM7g6bZOF6+Pkb5ab7sNboXq3evpnyym+zTArLC90bPNyibXJaWtVoy6rJR/o70yYnJ/oDMmPyIzZqy0KAsMdGCMmPilKqOB8aHpA0N2N4AXJDLuY8Dj4dJ346rOSsU4nWFy0/z5bgl4wCCZmA3heu8E89jwe0Ljp7RmAjFZk1ZaPNlcrIFZcaYqJHf5svAfL6aMmNM9InNoCy0psyCMmNMFMmr+XLMgjEs37E8KC09M3v1khPKn1C4hTPGFJr4CMpEbJ4yY0zUyK35MiMrg6s+vYpOI4IXfj6cedi/7Zux3RgTfWIzKAttvszMtJoyY0zUCNd8+ev6X2k51E0iuu3AtqD8hzIO+bd9s/kbY6JP7Hf0v/xyWLnSgjJjTNTwNV8G1pSd8Xb2QgRVSlcJyh8YlNWpUKeQS2eMKSyxWVMWGJS9/jokJVlQZoyJGr7my9ymxMgtKLvt9NtsfUNjolhsBmWBzZcJCe5lQZkxJkr4O/oHNF8GLh5etXTVoPy+oOz8k84vgtIZYwpLbAZlgTVliYkWlBljooqvT1lg86UELONZIaVCUH5fUJaalFoEpTPGFJaIgjIR6S4iS0RkmYg8FOa4iMhr3vG5ItIm4NjdIjJfRBaIyD0B6U+IyHoRme29ehbIJ4LgoMxqyowxUSZc8+WhjENc3uxy2p3QjoMZB4PyW1BmTGw4alAmIonAG0APoBnQV0SahWTrATT2Xv2BId65zYFbgPZAS+AiEWkccN7LqtrKe42noAQ2X/pqymxKDGNMlAjXfHk48zANKjagapmqHDxiQZkxsSiSmrL2wDJVXaGq6cBooFdInl7Ae+pMByqJSG2gKTBdVQ94a9BNAXoXYPnDC60ps2WWjDFRJFzz5aGMQ6QkpZCalMqMDTPYsn9L0DGwoMyYaBdJUFYHWBuwv85LiyTPfKCLiFQVkTJATyBwEp0BXnPnCBGpHO7mItJfRGaKyMytW7dGUFysT5kxJqqFNl9mZGWQpVmkJqX6a8n+b8z/+fNbUGZMbIgkKJMwaaHjtMPmUdVFwLPAd8C3wBwgwzs+BDgJaAVsBF4Md3NVHaaqbVW1bfXq1SMoLjb60hgT1UKbL31BV0piCrsO7QLgj+1/+PNbUGZMbIgkKFtHcO1WXWBDpHlUdbiqtlHVLsAOYKmXvllVM1U1C3gL10xaMKymzBgTxUKbLw9nuGWUUpNS2X5wOwClEkr58/tm+LegzJjoFklQNgNoLCINRSQZ6AOMC8kzDrjeG4XZAditqhsBRKSG954GXAZ85O3XDji/N66ps2DY6EtjTBQLbb7015QlpbDj4A4AkhKyF2QZ8fsIWtZsGTSXmTEm+hx1mSVVzRCRAcAEIBEYoaoLROQ27/hQYDyuv9gy4ADQL+ASY0WkKnAEuENVd3rpz4lIK1xT6Crg1gL5RGDNl8aYqBbafOlbcDw1KZWTKp/EjoM7SExI9Offsn8Llze73H+eMSY6RbT2pTddxfiQtKEB2wrckcu5nXNJvy7yYuZTQkLOfZsSwxgTJUKbLwP7lH3Z90vOHHEmuw/v9uffl77PllcyJgbE5tcqCRl3YDVlxpgoEtp8GdinrGa5mlzW9DL2pe8DIDMrk4MZBy0oMyYGxEdQZvOUGWOiSG6jL30d+cuWKsuhjENkZmUyd/NcAAvKjIkBsRmUhbKaMmNMFMkx+tLrU5aSlAJA2eSyANzw+Q20GeZWtbOgzJjoZ0GZMcaUMLmNvgysKQMYNW+U/xwLyoyJfhaUGWNimoh0F5ElIrJMRB4Kc7yiiHwpInNEZIGI9PPSm4jI7IDXHhG5xzv2hIisDzjWsyDLnGP0pdenLCUxuKYskAVlxkS/iEZfRj0LyoyJSyKSCLwBnI+b5HqGiIxT1YUB2e4AFqrqxSJSHVgiIqNUdQluxRHfddYD/wk472VVfaGQyg3kHH0ZWlMWyIIyY6Jf/NSU2ZQYxsSj9sAyVV2hqunAaKBXSB4FyouLhMrhVh7JCMnTDViuqqsLu8AQZvRlLn3KAllQZkz0i5+gzGrKjIlHdYC1AfvrvLRAg4GmuKXh5gF3e8u/BeqDtxpJgAEiMldERohI5XA3F5H+IjJTRGZu3bo14kLn1nyZV01ZhZQKEV/fGFMyxUdQZlNiGBOvJEyahuxfCMwGTsA1Vw4WEX+E4y0vdwnwScA5Q4CTvPwbgRfD3VxVh6lqW1VtW7169cgLncfksQBlSpXJcU5axbSIr2+MKZniIyizmjJj4tU6oF7Afl1cjVigfsBn6iwDVgKnBBzvAfymqpt9Caq6WVUzvRq1t3DNpAUmt+ZLX01ZVo6KvPCBmjEmulhQZoyJZTOAxiLS0Kvx6gOMC8mzBtdnDBGpCTQBVgQc70tI06WI1A7Y7Q3ML8hC5zZ5rK9PWd0KdQvydsaYEsKCMmNMzFLVDGAAMAFYBIxR1QUicpuI3OZlewroJCLzgEnAg6q6DUBEyuBGbn4WcunnRGSeiMwFzgHuLchy55g8NuMwiZJIUoIbMF+7fG1GXDLCn//Dyz4syNsbY4qJTYlhjIlpqjoeGB+SNjRgewNwQS7nHgCqhkm/roCLGSTc5LG+WjKfamWq+bf7nta3MItjjCkiVlNmjDElTI7Rl5mH/f3JfKwPmTGxJz6CslKlID29uEthjDERCTf60jfy0qd0qdJFXi5jTOGKj6AsNRUOHSruUhhjTETCjb4MrSmrlFqpqItljClk8RGUlS4NGRnuZYwxJVy40ZehfcqaVmsKQOMqjYu2cMaYQhMfHf1TvW+Yhw9DUnx8ZGNM9Ao3+jK0pkxE2Pvw3rBzlhljolN8RCi+oOzQISibc3kSY4wpScKOvgzpUwa23qUxsSY+mi99QdnBg8VbDmOMiUBo82V6ZjrJicnFWSRjTBGIr6DMOvsbY6JAaPNlRlaGf+JYY0zsio+grLQ3dNyCMmNMFAhtvszUTBITEouzSMaYIhAfQZnVlBljokho82VmViaJYkGZMbHOgjJjjClhQpsvrabMmPgQX0GZdfQ3xkSBHM2XVlNmTFyIr6DMasqMMVEgtPnSOvobEx8iCspEpLuILBGRZSLyUJjjIiKvecfnikibgGN3i8h8EVkgIvcEpFcRke9EZKn3XrlAPlE41tHfGBNFrPnSmPh01KBMRBKBN4AeQDOgr4g0C8nWA2jsvfoDQ7xzmwO3AO2BlsBFIuJbE+QhYJKqNgYmefuFw2rKjDFRxJovjYlPkdSUtQeWqeoKVU0HRgO9QvL0At5TZzpQSURqA02B6ap6QFUzgClA74BzRnrbI4FLj++j5MGCMmNMFMkx+tJqyoyJC5EEZXWAtQH767y0SPLMB7qISFURKQP0BOp5eWqq6kYA771G/osfIevob4yJIjmaL62mzJi4EEnPUQmTppHkUdVFIvIs8B2wD5gDZOSngCLSH9ckSlpaWuQnjhoFVaq4baspM8ZEEZs81pj4FElN2Tqya7cA6gIbIs2jqsNVtY2qdgF2AEu9PJu9Jk689y3hbq6qw1S1raq2rV69egTF9Vx9NXTv7rYtKDPGRJFwoy+tpsyY2BdJUDYDaCwiDUUkGegDjAvJMw643huF2QHY7WuaFJEa3nsacBnwUcA5N3jbNwBfHNcnyUtiIpQqZUGZMSYqhGu+tCkxjIl9R/1XrqoZIjIAmAAkAiNUdYGI3OYdHwqMx/UXWwYcAPoFXGKsiFQFjgB3qOpOL30QMEZEbgLWAFcU0GcKLzXVgjJjTFQI23xpNWXGxLyIvnqp6nhc4BWYNjRgW4E7cjm3cy7p24FuEZf0eKWmWkd/Y+KQiHQHXsV9qXxbVQeFHK8IfACk4Z6JL6jqOyLSBPg4IOuJwD9U9RURqeIdawCsAq4M+MJZEGUGQta+tD5lxsS8+JjRH6ymzJg4FOE8i3cAC1W1JdAVeFFEklV1iaq2UtVWwOm4VoD/eOcU+jyLggRPHms1ZcbEPAvKjDGxLJJ5FhUoL656qhxuQFLoKPFuwHJVXe3tF/o8i4oy7LdhgNWUGRMv4icoK13agjJj4k8k8ywOxk10vQGYB9yt6lVRZetD9iAliHCeRRHpLyIzRWTm1q1b81VwQdiy3w1Kt9GXxsSH+AnKrKbMmHgUyTyLFwKzgROAVsBgEangv4AbdX4J8El+b37MU/oAj3Z51N/h3+YpMyY+xFdQVhAd/QcPhjVrjv86xpiiEMk8i/2Az7xl4pYBK4FTAo73AH5T1c0BaRHNs3g8EiQBRVFVmxLDmDgRX0HZ8daUbdsGd94J3Ypu0Kgx5rhEMs/iGryR4CJSE2gCrAg43pfgpksognkWfc2VmZqJotZ8aUwcsKAsP7Zvd+/LloGGtoAYY0oaVc0AfPMsLgLG+OZZ9M21CDwFdBKRebiRlA+q6jYAb83e84HPQi49CDhfRJZ6xwdRwHyz+h/JPAJgzZfGxIH4qQ8vXfr4my99QRnA559D797Hdz1jTKGLYJ7FDcAFuZx7AKgaJr3Q51n0BWHpmelu32rKjIl58VNTlpwMR44c3zUCg7K5c4/vWsYYkwdfTZk/KLOaMmNiXvzUlCUlQUbo1EMReuwxqFEDypXLTrPO/saYQuSrGbOaMmPihwVlkfjnP937M8+492bNYPXq3PMbY8xx8vcpy7I+ZcbEi/hpvjyeoMxnxgxITIQWLWD58oIplzHGhGF9yoyJPxaU7d+f90jKrICJvefPh/LloWVLWLUKHnwQ0tMLvKjGGBM6+tLmKTMm9sV3ULZtm+sn9uyzuZ+3Z0/29tKl7r1NG/f+3HMwdWrBltMYYwjTp8yaL42JefEVlIWOvtzgTez98MO59xHbtSt4Pz0dzj0X/vxnt79tW0GW0hhjgDCjL6350piYFz9BWalSOWvKApst77or/Hk7dwbvZ2S4AO9f/3L7FpQZYwpBjj5lVlNmTMyLn6DM13wZGIgFTiab2yCA0JoyX74qVdx74NxlxhhTQHKMvrSaMmNiXnwFZRDccX///uzt3IKy0KDLd35yMlSoYDVlxphCYX3KjIk/8ReUBQZfgUFZbrP9+4Kun37KeaxqVVi0CP7974IpozHGeKxPmTHxJ37GWAcGZSkpbjuvmrKpU90UGFu3uv1GjXJes25d+O479+reHerXL/hyG2PiUmifMpsSw5jYZzVlPqFBWefO8Je/uJqyChWgWjWX7utLBnDGGdnbgVNnGGPMcQqdp8yaL42JfRaU+eTWfPnaay7gSkiAUaPg11+zj517bvZ26ChNY4w5Drb2pTHxJ36CslKl3HtuQVngSMzcXH01nHRS9n737tCundvesSM47yefwPTpx1ZWY0zc89WUHco4BECpxFLFWRxjTBGIn6DMV1MWWCMWGJSFTn0R6Msvw6eLwJgxbjuwpkwVrrwSOnaEfv2CR3xGStX1VcvMzP+5xpio52uuPJjhvjCmJKYUZ3GMMUUg/oKywJqyAweyt/MKyi66KPdjvj5mgTVlq1Zlb7/7bvZggUjMmQPPPAPjxsEFF8DgwZGfa4yJGb6asgNH3HMqJcmCMmNiXXwHZYdcswDdurlas7//HUaOdGlpae595sy8r1u+PCQmBgdl8+YF51m/PrIyHjwIrVu7crzxhktbu9a9T5sGK1dGdp2S5MABeP11WLiwuEtiTFTx9SE7eMRqyoyJFxaU1asHl17q9p95JntNy6wst3366XlfVwRq1IDNm7PTNm4MztO7d2RlHDgwe8WB777LLmNmJnTqBCee6NbeLG6qR2+SVXUB2S23uCWsTj3VjWK9+2537PvvYehQN8/bsmXBtZbRSBXGjnU1ncYUAKspMyb+RBSUiUh3EVkiIstE5KEwx0VEXvOOzxWRNgHH7hWRBSIyX0Q+EpFUL/0JEVkvIrO9V8+C+1hh5BaUpaZCpUo58+/fD+XKRXbtunWza7QgZ3PlmjWR9Q1bsSJ82rp12ftz50ZWpsKyYoX7vImJ8MAD4fMcPgxPPAFly8KHH0LXrq5/3d69bjTrmDGudvIvf4FmzaBxY5f3ootc37z0dBgypHiXsMrKgt9+gx9/dGUKbJIO9MUXrlbzggvg8suhV6/IBo0YcxTWp8yY+HPUoExEEoE3gB5AM6CviDQLydYDaOy9+gNDvHPrAHcBbVW1OZAI9Ak472VVbeW9xh/vh8lTXkFZmTI58+/f7wKFSNSrFxw4bd3qaoUC75VXnzWfPXtcH7VRo7LTvvkmuyYP4K23srcXLYKbbiq6Wqbdu13QsWGD23/+eZg92wVbq1e7tKeecj/TgQPdUlQffAD//S/8/LMLtlq3hj4BfwIJCfDcc6427bvvXKD20Udw++3QsqW7Z2FKT3dNwz/+6GpK//c/eOklF3Sefjp06eJ+Jw0bwowZwWunTpzofjcDBrjP2L27+znUr+9+N1lZwflNsYjgS2VFEflSROZ4XyD7BRyrJCKfishiEVkkIh299EL/Umk1ZcbEn0hqytoDy1R1haqmA6OBXiF5egHvqTMdqCQitb1jSUBpEUkCygAbCqjs+RNuSgxfUBY6W39GhvvPOtKgrG5d12dq+HC3v3UrVK/u/mN/7z2XFkmtz4oVrgbpssvg+utdQAYu8AE46ywYNgx+/93tDx4MI0bAs89GVs7j9eabbpWDd9/Nvmfr1i4AbdDA9Xn7xz+y82/eDNdc434O4H4HEye6Eangjv36K/ztb/Dqq3D//fDxx9k1cBs2uGDtxx/h669d8DlwYGQBbiSmTYPrrnNNw126uL58Z5/tyuFTuXL2dvv2LugE9/fxwAMuAJs3zwWon3wCPXq433+LFu7cs8+2wKwYRfil8g5goaq2BLoCL4pIsnfsVeBbVT0FaAksCjivUL9U+vuUWU2ZMXEjkqCsDhDQNsc6L+2oeVR1PfACsAbYCOxW1YkB+QZ4zZ0jRCTgf79CkFdNWYsWcP752en79rn3SIOyBg3c+803uw7/vqAMst+PtnB5VpZrImvY0JVp5EhX8/Kvf7njjRq5qTlEoE0bV2vjm4Zj4EDXZ8v32dLTYelSF8QsWhR8j1tvdctMffVVZJ8t0JdfulUMbrjBXefaa936n75BESee6N67dHHLVIVrFq5WzQWSmza5gDWwz54vWNuyxQV+99zj8nTp4po2y5aFxx+H5s1dE+nx+OorF4z5pjS55RYX7A4bBldc4QJMVRdMB06J8sILruwnneT6j738sivPX//qmrs//NAFbt26uZrPH390tW/hLF4M//ynC+aP1kfPNyjF5FckXyoVKC8iApQDdgAZIlIB6AIMB1DVdFXdVVQFD60pS05Mziu7MSYGRBKUSZi00K/+YfN4gVYvoCFwAlBWRK71jg8BTgJa4QK2F8PeXKS/iMwUkZlb8zO1RKhwQdnhwy4AAlfb4+MLoHxLKx3NKadkb0+a5GrNfIGa7xpHqynbsMEFU77Axueqq1zN2dixLsh57TWX/uOP7j4tW0KdOm578mTXt612bTj5ZBfMNGsGn3/uzvnkExd0pKfDxRfnb/60gwfdSNSzz3b7FSvC+++7n5Wv6dLnk0/gzDPzvl7Nmq7pMlDjxtnbvXu72riRI13gE2j9enf/KVOC0zMyXDDXp4/r67Vxoxv5uXGjC5aHDXN5Fi1ynz/QsGHQqpULzsaMyf79ibiAcOFCuO8+11R70kmuubp375yDOCpVgkcfhW+/dcF9/fquT93zz7t7v/ii63s2frz7/Tz2mAvm//Y3F3h99JHrNzhrluvTdvHFrgylS8OddxZcLWH8iORL5WCgKa4Wfx5wt6pmAScCW4F3ROR3EXlbRAK/qRXql0p/nzLf6EtrvjQm9qlqni+gIzAhYP9h4OGQPP8G+gbsLwFqA1cAwwPSrwfeDHOPBsD8o5Xl9NNP12M2ebIqqH7/fXZa69aqF1/stq+4wh335QHVb76J7NorV2afe+WV7n34cHdsxQq3P2JE3teYMsXlmzjx6PerXFm1f3/V1FTV++5T3bdPVUT1wQezyxH4+utf3Xnnnx+c/tZbud9j6VLVBQvcdlaW6u23u3O+/DJ8/ttvV23YUHXXrqOXPy/ff6/6xhs509esUf3xR9UDB1QffVS1UiVXnq+/Vn3uOfd7fPrp7M9Wvrzq2Wfn/Fn066fas6dqQoLq2rWqb7+t+u23kZXtwIHs61x1VWSf9fffVWvUCC5DcnL29rRpqq1ahf+9+V5padnbpUqp3nWXap8+qtdd5/5GZ85UzcjIz085qgAz9SjPhtxe3jPo7YD964DXQ/JcDryM+3LZCFgJVADaAhnAGV6+V4GnvO2auD6yCcDTwIhc7t8fmAnMTEtLy9fn/mnNT8oTaKfhnZQn0IzM2P0dGxOr8vv8iuShlgSswNV2JQNzgFND8vwJ+MZ7qHUAfvXSzwAW4PqSCTASuNM7Vjvg/HuB0Ucry3EFZVOn5gx6mjZ1wZhqdjAFqsOGuffffovs2pmZqrfeGvwf6fr17tj+/W7/6afzvsa777p8S5ce/X7t2uUMrBo0UC1XzqW1aKHapEl2nssvd3mqV1e9+WYXZLVpo9q8udv2+fRTFyD4ygLu+KefZu/v2BG+TFlZRRsYLF6cexDz+ed5Bzmgesopx3bfBx9UvfFG1cOHIz/n4EHVIUNUzzlHdfBg9zfRr5/qgAHu+NSpqs2auXI1b67asaNq/fqq556rOnu2y5OVpTpjhuqf/+wCcFBNTMz+PF27ql59tTvnvfeCf69R7jiDski+VH4NdA7Y/x7X7FkLWBWQ3hn4Osw9CuVL5fS105Un0NZDW2vik4nH8qMzxhSzAg/K3DXpCfwBLAf+7qXdBtzmbQuuM+1yXPV/24BznwQWA/OB94EUL/19L+9cYFxgkJbb67iCsunT3ccdPz47rWFDV9ug6moefP/B3XdfcGAVKV+w1KJFcHrVqqq33Zb3uf/4h6u9ieQ/+379ssv6448urXv37LTt27Pz+mqLFi50788849KHD3f7333n9hctCh+8zJyZHbAOHRrRj6HIvPmmao8ertbw++9VH3nE/X4zMlxN1k03ueDtmmtUV61y6Z99plqxogs0S5q1a12AH0m+3bvd38qrr6qefLJq7dqudtD3e2vTxgVwr74a9QHacQZlkXypHAI84W3XBNYD1bz9H4Em3vYTwPPedqF/qZyxfobyBNrk9SZa5ukyx/rjM8YUo0IJykrK67iCspkz3ccdNy47rXZt1VtucdvXXJP9H9oFF7j39PT83eOSSzSoudCnVSvVP/0p73OvvdbVjkTiiSfcferWzf5P/PHHs8sf6JFHXJqvFu2jj1z6/v2udu2009y+79zA2hdwwSS48pmS79Ah97eQkpL9O7z7btW9e4u7ZMfseIIyd/pRv1SeAEz0viTOB64NOLeV1/w4F/gcqOylF/qXylkbZilPoGkvp2nlQZWP4ydojCku+X1+eb3f44BvSozABcl9oy/Bdab2mT/fzU3lOydSAwe6EZE33hicXq9e7pOP+qxc6UZeRmLAAFi+3HWA93WWv/ZaN9/XrbcG533ySXf/v/zF7Z92mnsvU8Z1XL/rruClpPbtc4up79zpRpEOHerSfSsdmJItJcVN3Hv//W6E6TffuOlGPvnEjRaNdPBKDFE3XcX4kLShAdsbgAtyOXc2rm9ZaPp1BVvKnHxTYhw4csA6+RsTJ+JnmSXf7Px797r3SZNc4OELagJHAm7Y4JZOyq+WLd30B02bBqfXq+fmIHvjjfBTOai66RFOPjmy+1St6qaKqFo1O61RI/d5QkcqJiXBbbe50X4//OCmzvDp6c136RvROW6cC1K/+MJ9jjffdNOFvPQSnHtuZGUzJUP58tC3rxuNOnasG4HaubObB65XL5gwobhLaI7CNyXGwSMHbY4yY+JE/NSUVazo3n0zxD/2mHv/6Sf3HlhTBjmnazgeaWluhYABA1yQFFqbtWmTmzLDV4t1rFLyeHD36JEz7cQT4YQT3NQWkH1/38/i3HNtLcdol5DgplR55x1Xg+tbTWHcOBewnXyyq6GtVatYi2ly8k2JceDIAZujzJg4ET81Zb55yHxBWatW7v1vf3Pvl18enH/HjoK7d7162dvh5lpbuNC9B9ZiFQURFyj6+ObmMrHnhhvcvGcDB7rF4M84wzVJd+rkJr+97jo3J9zAga5W7VisX+9WmejdG66+2s2HZ46Zr6ZMUVKTUou5NMaYohA/NWWlSrl+VL7JNzMy3CSrV17p9i+6yC0a/umnbsLWggzKatbM3v7jj5zH1693776Z8YvSww+7n8OxNNea6NKypXuBm1B44EA32fBXX7k1Sj/4wB0bOND9W3n0UfelJbQWOdAff7ggLjPTLSL/6afZx774Ajp0cF0Gbr/d+iXmk69PGUDpUqWLsSTGmKISP0EZuNnWfTVlu3Zl9zPzSUhwNWYVK8KgQQV333bt3LqVS5dmr1sZaNMm9x4YvBUl+88y/tSq5foMguvvOHGiWxKsVi0XpM2aBQ8+6Jr3zzrLDQgJbB7fuNEtJzVkSPB1L7zQnXfggFs+6o8/3Becfv3grbfcqgRNmrg1U02efDVlgNWUGRMn4isoq1jRBWWDB7vRaOFqphISCn4pmwoV3LJITz3l1m7ctSt4XchNm9y6jqFBojFF4cQT3WAQnzPPdEtwPfqoW6Zq3DgXZD3+uKsR+/BDeOghNyCmWzf3peP3313ftX79skct/+lP7n31ajci9N134eef3eAR66t4VL4+ZQClk6ymzJh4EJ9B2XPPuf2CbKKMxFlnuZGW06Zld7zPynIj4gLX3jSmuCUkwDPPwNNPuz5izzwD06e7NT0BKld2AVbHjke/Vv36bqDBs8+6UZ9NmhRu2WOE1ZQZE3/ip6M/uMBn9+7sYOzgwaK9f/v2kJjopijIynI1ZoMGuRqH4uhPZszRiMDbb7tF2H0BWf/+7m82koAsUI0abkBB+/YFX84YZH3KjIk/8VVTlprq5gnbv9/tZ2YW7f3LloXzz3d9bb7/3jVblinjpqV4772iLYsxkapWDebNg0WLoE4d1/SeV+d/UyCspsyY+BNfNWUpKa6zfXHyTe66cqWrqdu+Hf7978gnjjWmOCQmuqkzKle2gKyIWJ8yY+JP/AVlBw5k70e6rFFBCu1P07evm47DGGMCBNaUWVBmTHyIv6DM54orXEfloibi1iUEtx7mqFFFXwZjTIkX2KfMmi+NiQ/xG5RdcEHxLS3z/POuk3/9+tYUZIwJK6j50jr6GxMX4jco862FWRxEivf+xpgSL7DJ0mrKjIkP8RuUJcXXwFNjTHQplVjKv219yoyJD/EblB05UnzlMMaYfLCaMmPiQ/wGZb4Z9Y0xpoQrl2xLsBkTD+IrKPN1qn/wQShfvnjLYowxEaqQYsuwGRMP4isoy8py7zbi0RgTRSwoMyY+xFdQpureE+LrYxtjopsFZcbEh/iKTnxBmdWUGWOiiAVlxsSH+AzKrKbMmLghIt1FZImILBORh8IcrygiX4rIHBFZICL9Ao5VEpFPRWSxiCwSkY5eehUR+U5ElnrvlQvzM1hQZkx8iK/oxPqUGRNXRCQReAPoATQD+opIs5BsdwALVbUl0BV4UUSSvWOvAt+q6ilAS2CRl/4QMElVGwOTvP1CUz7FBiYZEw/iKyizmjJj4k17YJmqrlDVdGA00CskjwLlRUSAcsAOIENEKgBdgOEAqpquqru8c3oBI73tkcClhfkhkhJssmtj4kF8RSfnnBP8boyJdXWAtQH767y0QIOBpsAGYB5wt6pmAScCW4F3ROR3EXlbRMp659RU1Y0A3nuNcDcXkf4iMlNEZm7dujXfhb/o5IvyfY4xJnrFV1B29tlw8CB06VLcJTHGFI1wfRU0ZP9CYDZwAtAKGOzVkiUBbYAhqtoa2E8+mylVdZiqtlXVttWrV89n0eHzqz7n8KOH832eMSY6RRSURdBRVkTkNe/4XBFpE3DsXq/z7HwR+UhEUr30Iu0o65dqy5UYE0fWAfUC9uviasQC9QM+U2cZsBI4xTt3nar+4uX7FBekAWwWkdoA3vuWwih8YkIiyYnJR89ojIkJRw3KIuwo2wNo7L36A0O8c+sAdwFtVbU5kAj08c4p0o6yxpi4NANoLCINvc77fYBxIXnWAN0ARKQm0ARYoaqbgLUi0sTL1w1Y6G2PA27wtm8Avii8j2CMiReR9B71d5QFEBFfR9mFAXl6Ae+pqgLTvWHktQPuUVpEjgBlyP6W2gs30glcR9nJwIPH/lGMMSaYqmaIyABgAu5L4QhVXSAit3nHhwJPAe+KyDxcc+eDqrrNu8SdwCgvoFuBq1UDGASMEZGbcEHdFUX2oYwxMSuSoCxcR9kzIshTR1VnisgLuIfWQWCiqk708gR1lBWRXDvK4mrfSEtLi6C4xhiTTVXHA+ND0oYGbG8ALsjl3NlA2zDp2/Fq14wxpqBE0qcsko6yYfN4/cR6AQ1xnWjLisi1+Sng8XaUNcYYY4yJBpEEZZF0lM0tz3nASlXdqqpHgM+ATl6eIukoa4wxxhgTDSJpvvR3lAXW4zrKXh2SZxwwwOtvdgaw22uSXAN0EJEyuObLbsDMgHNuwPXNiKij7KxZs7aJyOoIygxQDdh21FwlT7SWG6K37FbuopefstcvzIIUlTh5fkH0lt3KXfSiteyF9vwS1dCWyDCZRHoCr5DdUfbpwI6y3kzYg4HuwAGgn6rO9M59ErgKyAB+B25W1cMiUhUYA6ThdZRV1R35KfxRyjxTVXP0BSnporXcEL1lt3IXvWgue1GI5p9PtJbdyl30orXshVnuiNbuiKCjrOLWjwt37uPA42HSraOsMcYYY4wnvmb0N8YYY4wpoWI5KBtW3AU4RtFabojeslu5i140l70oRPPPJ1rLbuUuetFa9kIrd0R9yowxxhhjTOGK5ZoyY4wxxpioEXNB2dEWTy/CcowQkS0iMj8gLddF2EXkYa/MS0TkwoD000VknnfsNW+kKyKSIiIfe+m/iEiDAihzPRH5QUQWeYvI3x0N5faumyoiv4rIHK/sT0ZL2b1rJ4rI7yLyVbSUW0RWefebLSK+0dYlvtwlXUl4hkXj88u7blQ+w+z5VWzlLnnPMFWNmRduyo7lwIlAMjAHaFZMZekCtAHmB6Q9BzzkbT8EPOttN/PKmoJb/WA5kOgd+xXoiFs14Rugh5d+OzDU2+4DfFwAZa4NtPG2ywN/eGUr0eX2riVAOW+7FPAL0CEayu5d7z7gQ+CraPhb8a61CqgWklbiy12SX5SQZxhR+PzyrhWVzzDs+VVc5V5FCXuGFek/9MJ+eT+UCQH7DwMPF2N5GhD8UFsC1Pa2awNLwpUTt3hyRy/P4oD0vsC/A/N420m4ieykgMv/BXB+FJa7DPAbbiLjEl923AoYk4BzyX6oRUO5V5HzgVbiy12SX5SgZxhR/vzyrh11zzDs+VVkP29K4DMs1povwy6MXkxlCSdoEXbAtwh7buWu422Hpgedo6oZwG6gakEV1KtmbY37xhYV5faq0Gfjluz6TlWjpeyvAA8AWQFp0VBuBSaKyCwR6R9F5S7JSvIzLKp+t9H2DLPnV7H8rZS4Z1hEk8dGkUgWTy+Jcit3Xp+n0D6riJQDxgL3qOoer3k8bNZcylAs5VbVTKCViFQC/iMizfPIXiLKLiIXAVtUdZaIdI3klFzKUBw/8zNVdYOI1AC+E5HFeeQtSeUuyaLxM5e43200PsPs+RU2Pa9zCkKJe4bFWk1ZJIunF6fcFmHPrdzrvO3Q9KBzRCQJqAgc9zJVIlIK9zAbpaqfRUu5A6nqLmAybtmvkl72M4FLRGQVMBo4V0Q+iIJyo6obvPctwH+A9tFQ7hKuJD/DouJ3G+3PMHt+FUm5gZL5DIu1oMy/eLqIJOM61o0r5jIF8i3CDsGLsI8D+ngjNRoCjYFfvarTvSLSwRvNcX3IOb5rXQ58r17D9bHy7jEcWKSqL0VLub2yV/e+YSIipYHzgMUlveyq+rCq1lXVBri/1+9V9dqSXm4RKSsi5X3bwAXA/JJe7ihQkp9hJf53G63PMHt+FcvfSsl8hhVEZ7mS9AJ64kbcLAf+Xozl+AjYCBzBRcs34dqSJwFLvfcqAfn/7pV5Cd7IDS+9rfeHshy36Ltvwt9U4BNgGW7kx4kFUOazcFWrc4HZ3qtnSS+3d90WuAXv53r3/YeXXuLLHnDfrmR3lC3R5caNDpzjvRb4/q2V9HJHw4sS8AwjCp9f3nWj8hmGPb+K42+lRD7DbEZ/Y4wxxpgSINaaL40xxhhjopIFZcYYY4wxJYAFZcYYY4wxJYAFZcYYY4wxJYAFZcYYY4wxJYAFZcYYY4wxJYAFZcYYY4wxJYAFZcYYY4wxJcD/AxJvPj4jQkvaAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for x in plot_list:\n",
    "    fig, ax = plt.subplots(1, 2, figsize=(10, 3))\n",
    "    display_cards(x['exist_card'])\n",
    "    ax[0].plot(x['count_list'], x['win_per'], color='red')\n",
    "    ax[1].plot(x['count_list'], x['loss_per'], color='green')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba7fa72d",
   "metadata": {
    "hidden": true
   },
   "source": [
    "### 同起手牌，不同玩家数量的模拟"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "486d197d",
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------------\n",
      "♣️A\n",
      "♦️5\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "display_cards(plot_list[0]['exist_card'])\n",
    "count = 3\n",
    "for x in plot_list:\n",
    "    fig, ax = plt.subplots(1, 2, figsize=(10, 3))\n",
    "    ax[0].plot(x['count_list'], x['win_per'], color='red')\n",
    "    ax[1].plot(x['count_list'], x['loss_per'], color='green')\n",
    "    ax[0].set_title(count)\n",
    "    count += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9018ddcd",
   "metadata": {},
   "source": [
    "## 主判别函数（1）——给定我方起始手牌、选择给底牌，模拟次数1w次"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "e92fbf92",
   "metadata": {
    "code_folding": [
     31,
     98
    ]
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dcdec032b43e414483e140d6903b301b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/10000 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------------\n",
      "♣️K\n",
      "♥️8\n",
      "-----------------\n",
      "玩家总数：6\n",
      "您的胜率约为：15.940%\n",
      "-----------------\n",
      "两对 22.900%\n",
      "单牌 19.830%\n",
      "一对 46.230%\n",
      "三条 4.500%\n",
      "同花 1.860%\n",
      "顺子 2.500%\n",
      "葫芦 1.990%\n",
      "四条 0.160%\n",
      "同花顺 0.030%\n"
     ]
    }
   ],
   "source": [
    "# 模拟次数、玩家人数、翻牌阶段\n",
    "simulation_time = 10000\n",
    "gamer_num = 6\n",
    "stage = 0\n",
    "\n",
    "# 获得总牌库【card_list】\n",
    "# A-♣️, B-♠️, C-♦️, D-♥️\n",
    "# 11-J, 12-Q, 13-K, 14-A\n",
    "\n",
    "card_list = []\n",
    "count_rank = []\n",
    "\n",
    "for color in ['A', 'B', 'C', 'D']:\n",
    "    for num in range(2, 15):\n",
    "        card_list.append({'color':color, 'num':num})\n",
    "\n",
    "# 获得自己的手牌\n",
    "exist_card = list(random.sample(card_list, 2))\n",
    "\n",
    "# 设置手牌\n",
    "# exist_card = [transfer_card('A14'), transfer_card('B14')]\n",
    "for x in exist_card:\n",
    "    card_list.remove(x)\n",
    "\n",
    "# 当前局数、失败局数、获胜局数、平局数、牌型统计\n",
    "count = 0\n",
    "count_loss = 0\n",
    "count_win = 0\n",
    "count_tie = 0\n",
    "my_types = []\n",
    "\n",
    "if stage == 0:\n",
    "\n",
    "    for i in notebook.tqdm(range(simulation_time)):\n",
    "\n",
    "        count += 1\n",
    "        othergamer_max_types = []\n",
    "        othergamer_cards = []\n",
    "        judge_tie = 0\n",
    "        judge_loss = 0\n",
    "\n",
    "        card_list_copy = card_list.copy()\n",
    "\n",
    "        # 随机模拟底牌\n",
    "        cards_todo_ = random.sample(card_list_copy, 5)\n",
    "\n",
    "        # 当前底牌下，自己能够组合的最大牌型\n",
    "        my_max_cards = get_max_type(cards_todo_, exist_card)\n",
    "        my_types.append(my_max_cards['rank'])\n",
    "        \n",
    "        # 排除底牌和自己手牌后，对手可能的手牌池\n",
    "        for x in list(cards_todo_):\n",
    "            card_list_copy.remove(x)\n",
    "\n",
    "        for x in range(gamer_num - 1):\n",
    "            opponent_cards = random.sample(card_list_copy, 2)\n",
    "            for m in opponent_cards:\n",
    "                card_list_copy.remove(m)\n",
    "                \n",
    "            # 当前底牌下，对手在某手牌中的最大牌型\n",
    "            opponent_max_cards = get_max_type(cards_todo_, opponent_cards)\n",
    "            othergamer_cards.append(opponent_max_cards)\n",
    "            othergamer_max_types.append(opponent_max_cards['rank'])\n",
    "\n",
    "        # 如果任何一家对手牌型更大，则输\n",
    "        if min(othergamer_max_types) < my_max_cards['rank']:\n",
    "            count_loss += 1\n",
    "            continue\n",
    "\n",
    "        for opponent_max_cards in othergamer_cards:\n",
    "\n",
    "            # 牌型相同，则同牌型比大小\n",
    "            if opponent_max_cards['rank'] == my_max_cards['rank']:\n",
    "                my_max_type = compare_samerank(my_max_cards['types_todo'])['out']\n",
    "                opponent_max_type = compare_samerank(opponent_max_cards['types_todo'])['out']\n",
    "                final_max_type = compare_samerank([my_max_type, opponent_max_type])['out']\n",
    "\n",
    "                # 只要出现judge_win=1，就说明至少有一家牌和自己同样大，这把就无法获胜\n",
    "                if final_max_type == my_max_type and final_max_type == opponent_max_type:\n",
    "                    judge_tie = 1\n",
    "                elif final_max_type == my_max_type:\n",
    "                    continue\n",
    "                else:\n",
    "                    count_loss += 1\n",
    "                    judge_loss = 1\n",
    "                    break\n",
    "\n",
    "            # 自己牌比对手牌大，比下一家\n",
    "            else:\n",
    "                continue\n",
    "\n",
    "        if judge_loss == 1:\n",
    "            continue\n",
    "        elif judge_tie == 0:\n",
    "            count_win += 1\n",
    "        else:\n",
    "            count_tie += 1\n",
    "\n",
    "else:\n",
    "    round_time = 2  # 1--Flop、2--Turn、3--River\n",
    "\n",
    "    # 起始三张公共牌\n",
    "    public_card = list(random.sample(card_list, 2+round_time))\n",
    "    # public_card = [transfer_card('B6'), transfer_card('B9'), transfer_card('C9')]\n",
    "    for x in public_card:\n",
    "        card_list.remove(x)\n",
    "\n",
    "    for i in notebook.tqdm(range(simulation_time)):\n",
    "        count += 1\n",
    "        othergamer_max_types = []\n",
    "        othergamer_cards = []\n",
    "        judge_tie = 0\n",
    "        judge_loss = 0\n",
    "        card_list_copy = card_list.copy()\n",
    "\n",
    "        cards_todo_ = random.sample(card_list_copy, 3-round_time)\n",
    "\n",
    "        # 排除底牌和自己手牌后，对手可能的手牌池\n",
    "        for x in list(cards_todo_):\n",
    "            card_list_copy.remove(x)\n",
    "\n",
    "        cards_todo_ = cards_todo_ + public_card\n",
    "\n",
    "        # 当前底牌下，自己能够组合的最大牌型\n",
    "        my_max_cards = get_max_type(cards_todo_, exist_card)\n",
    "        my_types.append(my_max_cards['rank'])\n",
    "\n",
    "        for x in range(gamer_num - 1):\n",
    "            opponent_cards = random.sample(card_list_copy, 2)\n",
    "            for m in opponent_cards:\n",
    "                card_list_copy.remove(m)\n",
    "                \n",
    "            # 当前底牌下，对手在某手牌中的最大牌型\n",
    "            opponent_max_cards = get_max_type(cards_todo_, opponent_cards)\n",
    "            othergamer_cards.append(opponent_max_cards)\n",
    "            othergamer_max_types.append(opponent_max_cards['rank'])\n",
    "\n",
    "        # 如果任何一家对手牌型更大，则输\n",
    "        if min(othergamer_max_types) < my_max_cards['rank']:\n",
    "            count_loss += 1\n",
    "            continue\n",
    "\n",
    "        for opponent_max_cards in othergamer_cards:\n",
    "\n",
    "            # 牌型相同，则同牌型比大小\n",
    "            if opponent_max_cards['rank'] == my_max_cards['rank']:\n",
    "                my_max_type = compare_samerank(my_max_cards['types_todo'])['out']\n",
    "                opponent_max_type = compare_samerank(opponent_max_cards['types_todo'])['out']\n",
    "                final_max_type = compare_samerank([my_max_type, opponent_max_type])['out']\n",
    "\n",
    "                # 只要出现judge_win=1，就说明至少有一家牌和自己同样大，这把就无法获胜\n",
    "                if final_max_type == my_max_type and final_max_type == opponent_max_type:\n",
    "                    judge_tie = 1\n",
    "                elif final_max_type == my_max_type:\n",
    "                    continue\n",
    "                else:\n",
    "                    count_loss += 1\n",
    "                    judge_loss = 1\n",
    "                    break\n",
    "\n",
    "            # 自己牌比对手牌大，比下一家\n",
    "            else:\n",
    "                continue\n",
    "\n",
    "        if judge_loss == 1:\n",
    "            continue\n",
    "        elif judge_tie == 0:\n",
    "            count_win += 1\n",
    "        else:\n",
    "            count_tie += 1\n",
    "\n",
    "display_cards(exist_card)\n",
    "if stage == 1:\n",
    "    display_cards(public_card)\n",
    "\n",
    "print('-----------------')\n",
    "print('玩家总数：{}'.format(str(gamer_num)))\n",
    "print('您的胜率约为：{}'.format('{:.3%}'.format(count_win/count)))\n",
    "print('-----------------')\n",
    "\n",
    "l = dict(Counter(my_types))\n",
    "rank_dict = {2:'同花顺', 3:'四条', 4:'葫芦', 5:'同花', 6:'顺子', 7:'三条', 8:'两对', 9:'一对', 10:'单牌'}\n",
    "l = dict(zip(list(map(lambda x:rank_dict[x], l.keys())), list(map(lambda x:'{:.3%}'.format(x/simulation_time), l.values()))))\n",
    "for x in l.keys():\n",
    "    print(x,l[x])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77022513",
   "metadata": {},
   "source": [
    "## 主判别函数（2）——给定各玩家手牌、底牌，获得每家玩家胜率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "7c3e3cdd",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8b0f81cb043c4e818baa52489d0fc0b2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/10000 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------------\n",
      "♠️5\n",
      "♦️6♦️Q\n",
      "-----------------\n",
      "玩家总数：5\n",
      "-----------------\n",
      "-----------------\n",
      "♦️4♦️7\n",
      "您的胜率约为：58.790%\n",
      "一对 24.310%\n",
      "同花 37.580%\n",
      "顺子 18.990%\n",
      "三条 1.410%\n",
      "单牌 10.310%\n",
      "两对 7.160%\n",
      "同花顺 0.240%\n",
      "-----------------\n",
      "♣️2♣️7\n",
      "您的胜率约为：5.710%\n",
      "一对 48.010%\n",
      "单牌 38.570%\n",
      "三条 1.350%\n",
      "两对 7.240%\n",
      "顺子 4.830%\n",
      "-----------------\n",
      "♣️8\n",
      "♠️7\n",
      "您的胜率约为：21.300%\n",
      "顺子 33.710%\n",
      "单牌 19.210%\n",
      "一对 36.750%\n",
      "两对 8.860%\n",
      "三条 1.470%\n",
      "-----------------\n",
      "♠️2\n",
      "♥️A\n",
      "您的胜率约为：3.810%\n",
      "单牌 35.280%\n",
      "一对 51.290%\n",
      "三条 1.790%\n",
      "两对 10.110%\n",
      "顺子 1.530%\n",
      "-----------------\n",
      "♠️10\n",
      "♦️10\n",
      "您的胜率约为：14.970%\n",
      "一对 43.650%\n",
      "同花 3.730%\n",
      "两对 41.080%\n",
      "葫芦 3.680%\n",
      "三条 7.760%\n",
      "四条 0.100%\n"
     ]
    }
   ],
   "source": [
    "# 模拟次数、玩家人数、翻牌阶段\n",
    "simulation_time = 10000\n",
    "gamer_num = 5\n",
    "stage = 1\n",
    "\n",
    "# 获得总牌库【card_list】\n",
    "# 手牌集合【hand_card_list】\n",
    "# A-♣️, B-♠️, C-♦️, D-♥️\n",
    "# 11-J, 12-Q, 13-K, 14-A\n",
    "\n",
    "card_list = []\n",
    "# count_rank = []\n",
    "hand_card_list = []\n",
    "\n",
    "for color in ['A', 'B', 'C', 'D']:\n",
    "    for num in range(2, 15):\n",
    "        card_list.append({'color':color, 'num':num})\n",
    "\n",
    "# 各方手牌集合\n",
    "for x in range(gamer_num):\n",
    "    hand_cards = random.sample(card_list, 2)\n",
    "    hand_card_list.append({'hand_card':hand_cards, 'rank_list':[], 'win_per':0, 'win_count':0})\n",
    "    for m in hand_cards:\n",
    "        card_list.remove(m)\n",
    "        \n",
    "# 当前局数、失败局数、获胜局数、平局数、牌型统计\n",
    "count = 0\n",
    "\n",
    "if stage == 0:\n",
    "\n",
    "    for i in notebook.tqdm(range(simulation_time)):\n",
    "        \n",
    "        ii = 0\n",
    "        count += 1\n",
    "        othergamer_max_types = []\n",
    "        othergamer_cards = []\n",
    "        judge_tie = 0\n",
    "        judge_loss = 0\n",
    "        judge_max_rank = []\n",
    "        judge_card_list = []\n",
    "        \n",
    "        # 随机模拟底牌\n",
    "        public_cards = random.sample(card_list, 5)\n",
    "        \n",
    "        for x in hand_card_list:\n",
    "            # 当前底牌下，自己能够组合的最大牌型\n",
    "            max_cards = get_max_type(public_cards, x['hand_card'])\n",
    "            \n",
    "            judge_max_rank.append(max_cards['rank'])\n",
    "            judge_card_list.append(max_cards)\n",
    "            x['rank_list'].append(max_cards['rank'])\n",
    "        \n",
    "        # 获得当前牌型最大的玩家索引\n",
    "        max_rank = min(judge_max_rank)\n",
    "        to_judge_index = []\n",
    "        for x in [z == max_rank for z in judge_max_rank]:\n",
    "            if x:\n",
    "                to_judge_index.append(ii)\n",
    "            ii += 1\n",
    "        \n",
    "        # 如果没有同最大牌型牌，则最大牌型获胜\n",
    "        if len(to_judge_index) == 1:\n",
    "            hand_card_list[to_judge_index[0]]['win_count'] += 1\n",
    "            continue\n",
    "        \n",
    "        # 首个参加比较的手牌为基础牌\n",
    "        my_max_type = compare_samerank(judge_card_list[to_judge_index[0]]['types_todo'])['out']\n",
    "        max_index = [to_judge_index[0]]\n",
    "        \n",
    "        for x in to_judge_index[1:-2]:\n",
    "            opponent_max_type = compare_samerank(judge_card_list[x]['types_todo'])['out']\n",
    "            final_max_type = compare_samerank([my_max_type, opponent_max_type])['out']\n",
    "\n",
    "            # 如果同样大，则记录下来，并比较下一家\n",
    "            if final_max_type == my_max_type and final_max_type == opponent_max_type:\n",
    "                max_index.append(x)\n",
    "                continue\n",
    "            # 如果自己牌更大，则继续比下一家\n",
    "            elif final_max_type == my_max_type:\n",
    "                continue\n",
    "            # 如果基础牌更小，则将下一家作为基础牌继续比较\n",
    "            else:\n",
    "                my_max_type = opponent_max_type\n",
    "                max_index = [x]\n",
    "                continue\n",
    "        for x in max_index:\n",
    "            hand_card_list[x]['win_count'] += 1\n",
    "\n",
    "else:\n",
    "    round_time = 1  # 1--Flop、2--Turn、3--River\n",
    "\n",
    "    # 起始三张公共牌\n",
    "    public_card = list(random.sample(card_list, 2 + round_time))\n",
    "    # public_card = [transfer_card('B6'), transfer_card('B9'), transfer_card('C9')]\n",
    "    for x in public_card:\n",
    "        card_list.remove(x)\n",
    "\n",
    "    for i in notebook.tqdm(range(simulation_time)):\n",
    "        ii = 0\n",
    "        count += 1\n",
    "        othergamer_max_types = []\n",
    "        othergamer_cards = []\n",
    "        judge_tie = 0\n",
    "        judge_loss = 0\n",
    "        judge_max_rank = []\n",
    "        judge_card_list = []\n",
    "\n",
    "        # 随机模拟底牌\n",
    "        public_cards = random.sample(card_list, 3 - round_time) + public_card\n",
    "\n",
    "        for x in hand_card_list:\n",
    "            # 当前底牌下，自己能够组合的最大牌型\n",
    "            max_cards = get_max_type(public_cards, x['hand_card'])\n",
    "\n",
    "            judge_max_rank.append(max_cards['rank'])\n",
    "            judge_card_list.append(max_cards)\n",
    "            x['rank_list'].append(max_cards['rank'])\n",
    "\n",
    "        # 获得当前牌型最大的玩家索引\n",
    "        max_rank = min(judge_max_rank)\n",
    "        to_judge_index = []\n",
    "        for x in [z == max_rank for z in judge_max_rank]:\n",
    "            if x:\n",
    "                to_judge_index.append(ii)\n",
    "            ii += 1\n",
    "\n",
    "        # 如果没有同最大牌型牌，则最大牌型获胜\n",
    "        if len(to_judge_index) == 1:\n",
    "            hand_card_list[to_judge_index[0]]['win_count'] += 1\n",
    "            continue\n",
    "\n",
    "        # 首个参加比较的手牌为基础牌\n",
    "        my_max_type = compare_samerank(judge_card_list[to_judge_index[0]]['types_todo'])['out']\n",
    "        max_index = [to_judge_index[0]]\n",
    "\n",
    "        for x in to_judge_index[1:-2]:\n",
    "            opponent_max_type = compare_samerank(judge_card_list[x]['types_todo'])['out']\n",
    "            final_max_type = compare_samerank([my_max_type, opponent_max_type])['out']\n",
    "\n",
    "            # 如果同样大，则记录下来，并比较下一家\n",
    "            if final_max_type == my_max_type and final_max_type == opponent_max_type:\n",
    "                max_index.append(x)\n",
    "                continue\n",
    "            # 如果自己牌更大，则继续比下一家\n",
    "            elif final_max_type == my_max_type:\n",
    "                continue\n",
    "            # 如果基础牌更小，则将下一家作为基础牌继续比较\n",
    "            else:\n",
    "                my_max_type = opponent_max_type\n",
    "                max_index = [x]\n",
    "                continue\n",
    "        for x in max_index:\n",
    "            hand_card_list[x]['win_count'] += 1\n",
    "            \n",
    "if stage == 1:\n",
    "    display_cards(public_card)\n",
    "\n",
    "print('-----------------')\n",
    "print('玩家总数：{}'.format(str(gamer_num)))\n",
    "print('-----------------')\n",
    "\n",
    "rank_dict = {2:'同花顺', 3:'四条', 4:'葫芦', 5:'同花', 6:'顺子', 7:'三条', 8:'两对', 9:'一对', 10:'单牌'}\n",
    "\n",
    "for z in hand_card_list:\n",
    "    z['win_count'] = z['win_count'] / simulation_time\n",
    "    l = dict(Counter(z['rank_list']))\n",
    "    l = dict(zip(list(map(lambda x:rank_dict[x], l.keys())), list(map(lambda x:'{:.3%}'.format(x/simulation_time), l.values()))))\n",
    "    z['rank_list'] = l\n",
    "    \n",
    "    display_cards(z['hand_card'])\n",
    "    print('您的胜率约为：{}'.format('{:.3%}'.format(z['win_count'])))\n",
    "    for m in z['rank_list'].keys():\n",
    "        print(m, z['rank_list'][m])\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90e64dc9",
   "metadata": {},
   "source": [
    "## 获得手牌信息后遍历所有可能，时间太长，现在遍历时间约：2118760次总循环，平均9次循环/1秒，预计时长211876s = 3531mins = 58h = 2.45days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "id": "7f5a1d9e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4b1346c6507748ea86ce4e7cc25e9b9a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "56.4465%\n",
      "57.4086%\n",
      "47.3433%\n",
      "39.5989%\n",
      "35.8445%\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m/var/folders/s2/hx0rrywn56l8fy0kbl1npysw0000gn/T/ipykernel_17030/1345951920.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     36\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     37\u001b[0m         \u001b[0;31m# 当前底牌下，对手在某手牌中的最大牌型\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 38\u001b[0;31m         \u001b[0mopponent_max_cards\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_max_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcards_todo_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mopponent_cards\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     39\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     40\u001b[0m         \u001b[0;31m# 如果对手牌型更大，则输\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/var/folders/s2/hx0rrywn56l8fy0kbl1npysw0000gn/T/ipykernel_17030/4038795016.py\u001b[0m in \u001b[0;36mget_max_type\u001b[0;34m(cards_todo, my_card)\u001b[0m\n\u001b[1;32m    288\u001b[0m             \u001b[0mrank\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmax_type\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'rank'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    289\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 290\u001b[0;31m         \u001b[0;32melif\u001b[0m \u001b[0mmax_rank\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m8\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mcheck_one_pair\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnums_\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m  \u001b[0;31m# rank:9\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    291\u001b[0m             \u001b[0mmax_type\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_one_pair\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnums_\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    292\u001b[0m             \u001b[0mrank\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmax_type\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'rank'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/var/folders/s2/hx0rrywn56l8fy0kbl1npysw0000gn/T/ipykernel_17030/4038795016.py\u001b[0m in \u001b[0;36mcheck_one_pair\u001b[0;34m(nums)\u001b[0m\n\u001b[1;32m     95\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     96\u001b[0m                 \u001b[0msingle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 97\u001b[0;31m         \u001b[0msingle\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msorted\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msingle\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     98\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     99\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m'rank'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;36m9\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'pair'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mpair\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'single_low'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0msingle\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'single_middle'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0msingle\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'single_high'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0msingle\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m}\u001b[0m  \u001b[0;31m# 一对，先比对子，再比单牌 rank:9\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "# 获得总牌库\n",
    "# A-♣️, B-♠️, C-♦️, D-♥️\n",
    "# 11-J, 12-Q, 13-K, 14-A\n",
    "\n",
    "card_list = []\n",
    "\n",
    "for color in ['A', 'B', 'C', 'D']:\n",
    "    for num in range(2, 15):\n",
    "        card_list.append({'color':color, 'num':num})\n",
    "\n",
    "# 设置手牌\n",
    "exist_card = [transfer_card('A1'), transfer_card('C5')]\n",
    "for x in exist_card:\n",
    "    card_list.remove(x)\n",
    "\n",
    "count = 0\n",
    "count_loss = 0\n",
    "count_win = 0\n",
    "count_tie = 0\n",
    "\n",
    "# 遍历所有可能底牌\n",
    "for cards_todo_ in notebook.tqdm(itertools.combinations(card_list, 5)):\n",
    "    \n",
    "    count += 1\n",
    "    card_list_copy = card_list.copy()\n",
    "    \n",
    "    # 当前底牌下，自己能够组合的最大牌型\n",
    "    my_max_cards = get_max_type(cards_todo_, exist_card)\n",
    "    \n",
    "    # 排除底牌和自己手牌后，对手可能的手牌池\n",
    "    for x in list(cards_todo_):\n",
    "        card_list_copy.remove(x)\n",
    " \n",
    "    for opponent_cards in itertools.combinations(card_list_copy, 2):\n",
    "        \n",
    "        # 当前底牌下，对手在某手牌中的最大牌型\n",
    "        opponent_max_cards = get_max_type(cards_todo_, opponent_cards)\n",
    "        \n",
    "        # 如果对手牌型更大，则输\n",
    "        if opponent_max_cards['rank'] < my_max_cards['rank']:\n",
    "            count_loss += 1\n",
    "            \n",
    "        # 牌型相同，则同牌型比大小\n",
    "        elif opponent_max_cards['rank'] == my_max_cards['rank']:\n",
    "            my_max_type = compare_samerank(my_max_cards['types_todo'])['out']\n",
    "            opponent_max_type = compare_samerank(opponent_max_cards['types_todo'])['out']\n",
    "            final_max_type = compare_samerank([my_max_type, opponent_max_type])['out']\n",
    "            \n",
    "            if final_max_type == my_max_type and final_max_type == opponent_max_type:\n",
    "                count_tie += 1\n",
    "            elif final_max_type == my_max_type:\n",
    "                count_win += 1\n",
    "            else:\n",
    "                count_loss += 1\n",
    "        \n",
    "        else:\n",
    "            count_win += 1\n",
    "    \n",
    "    # 总时间太长，每200次循环输出一次胜率，虽然没啥用\n",
    "    if count % 200 == 0:\n",
    "        print('{:.4%}'.format(count_win/sum([count_win,count_loss,count_tie])))"
   ]
  }
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